[{"day":"21","quality_controlled":"1","tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","image":"/images/cc_by.png","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","short":"CC BY (4.0)"},"has_accepted_license":"1","project":[{"_id":"2646861A-B435-11E9-9278-68D0E5697425","name":"Control of embryonic cleavage pattern","call_identifier":"FWF","grant_number":"I03601"}],"publisher":"eLife Sciences Publications","type":"journal_article","external_id":{"isi":["000733610100001"]},"date_published":"2021-12-21T00:00:00Z","ddc":["570"],"language":[{"iso":"eng"}],"status":"public","isi":1,"month":"12","acknowledgement":"We thank members of the Heisenberg and McDougall groups for technical advice and discussion. We are grateful to the Bioimaging and Nanofabrication facilities of IST Austria and the Imaging Platform (PIM) and animal facility (CRB) of Institut de la Mer de Villefranche (IMEV), which is supported by EMBRC-France, whose French state funds are managed by the ANR within the Investments of the Future program under reference ANR-10-INBS-0, for continuous support. This work was supported by a collaborative grant from the French Government funding agency Agence National de la Recherche to McDougall (ANR 'MorCell': ANR-17-CE 13-0028) and the Austrian Science Fund to Heisenberg (FWF: I 3601-B27).","publication_identifier":{"eissn":["2050-084X"]},"article_type":"original","scopus_import":"1","doi":"10.7554/eLife.75639","article_processing_charge":"No","oa_version":"Published Version","file_date_updated":"2022-01-10T09:40:37Z","publication_status":"published","title":"Combined effect of cell geometry and polarity domains determines the orientation of unequal division","abstract":[{"lang":"eng","text":"Cell division orientation is thought to result from a competition between cell geometry and polarity domains controlling the position of the mitotic spindle during mitosis. Depending on the level of cell shape anisotropy or the strength of the polarity domain, one dominates the other and determines the orientation of the spindle. Whether and how such competition is also at work to determine unequal cell division (UCD), producing daughter cells of different size, remains unclear. Here, we show that cell geometry and polarity domains cooperate, rather than compete, in positioning the cleavage plane during UCDs in early ascidian embryos. We found that the UCDs and their orientation at the ascidian third cleavage rely on the spindle tilting in an anisotropic cell shape, and cortical polarity domains exerting different effects on spindle astral microtubules. By systematically varying mitotic cell shape, we could modulate the effect of attractive and repulsive polarity domains and consequently generate predicted daughter cell size asymmetries and position. We therefore propose that the spindle position during UCD is set by the combined activities of cell geometry and polarity domains, where cell geometry modulates the effect of cortical polarity domain(s)."}],"citation":{"ama":"Godard BG, Dumollard R, Heisenberg C-PJ, Mcdougall A. Combined effect of cell geometry and polarity domains determines the orientation of unequal division. <i>eLife</i>. 2021;10. doi:<a href=\"https://doi.org/10.7554/eLife.75639\">10.7554/eLife.75639</a>","ista":"Godard BG, Dumollard R, Heisenberg C-PJ, Mcdougall A. 2021. Combined effect of cell geometry and polarity domains determines the orientation of unequal division. eLife. 10, e75639.","ieee":"B. G. Godard, R. Dumollard, C.-P. J. Heisenberg, and A. Mcdougall, “Combined effect of cell geometry and polarity domains determines the orientation of unequal division,” <i>eLife</i>, vol. 10. eLife Sciences Publications, 2021.","mla":"Godard, Benoit G., et al. “Combined Effect of Cell Geometry and Polarity Domains Determines the Orientation of Unequal Division.” <i>ELife</i>, vol. 10, e75639, eLife Sciences Publications, 2021, doi:<a href=\"https://doi.org/10.7554/eLife.75639\">10.7554/eLife.75639</a>.","chicago":"Godard, Benoit G, Remi Dumollard, Carl-Philipp J Heisenberg, and Alex Mcdougall. “Combined Effect of Cell Geometry and Polarity Domains Determines the Orientation of Unequal Division.” <i>ELife</i>. eLife Sciences Publications, 2021. <a href=\"https://doi.org/10.7554/eLife.75639\">https://doi.org/10.7554/eLife.75639</a>.","short":"B.G. Godard, R. Dumollard, C.-P.J. Heisenberg, A. Mcdougall, ELife 10 (2021).","apa":"Godard, B. G., Dumollard, R., Heisenberg, C.-P. J., &#38; Mcdougall, A. (2021). Combined effect of cell geometry and polarity domains determines the orientation of unequal division. <i>ELife</i>. eLife Sciences Publications. <a href=\"https://doi.org/10.7554/eLife.75639\">https://doi.org/10.7554/eLife.75639</a>"},"article_number":"e75639","year":"2021","date_created":"2022-01-09T23:01:26Z","file":[{"file_name":"2021_eLife_Godard.pdf","access_level":"open_access","success":1,"file_size":7769934,"relation":"main_file","date_updated":"2022-01-10T09:40:37Z","date_created":"2022-01-10T09:40:37Z","creator":"alisjak","file_id":"10611","content_type":"application/pdf","checksum":"759c7a873d554c48a6639e6350746ca6"}],"_id":"10606","user_id":"4359f0d1-fa6c-11eb-b949-802e58b17ae8","author":[{"first_name":"Benoit G","last_name":"Godard","id":"33280250-F248-11E8-B48F-1D18A9856A87","full_name":"Godard, Benoit G"},{"last_name":"Dumollard","first_name":"Remi","full_name":"Dumollard, Remi"},{"id":"39427864-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-0912-4566","full_name":"Heisenberg, Carl-Philipp J","first_name":"Carl-Philipp J","last_name":"Heisenberg"},{"full_name":"Mcdougall, Alex","last_name":"Mcdougall","first_name":"Alex"}],"volume":10,"oa":1,"acknowledged_ssus":[{"_id":"NanoFab"},{"_id":"Bio"}],"intvolume":"        10","date_updated":"2023-08-17T06:32:44Z","publication":"eLife","department":[{"_id":"CaHe"}]},{"date_created":"2022-01-09T23:01:26Z","file":[{"creator":"alisjak","file_id":"10612","content_type":"application/pdf","checksum":"360681585acb51e80d17c6b213c56b55","access_level":"open_access","success":1,"file_name":"2021_Parkinsonism_Venezia.pdf","date_updated":"2022-01-10T13:41:40Z","date_created":"2022-01-10T13:41:40Z","relation":"main_file","file_size":6848513}],"_id":"10607","abstract":[{"lang":"eng","text":"The evidence linking innate immunity mechanisms and neurodegenerative diseases is growing, but the specific mechanisms are incompletely understood. Experimental data suggest that microglial TLR4 mediates the uptake and clearance of α-synuclein also termed synucleinophagy. The accumulation of misfolded α-synuclein throughout the brain is central to Parkinson's disease (PD). The distribution and progression of the pathology is often attributed to the propagation of α-synuclein. Here, we apply a classical α-synuclein propagation model of prodromal PD in wild type and TLR4 deficient mice to study the role of TLR4 in the progression of the disease. Our data suggest that TLR4 deficiency facilitates the α-synuclein seed spreading associated with reduced lysosomal activity of microglia. Three months after seed inoculation, more pronounced proteinase K-resistant α-synuclein inclusion pathology is observed in mice with TLR4 deficiency. The facilitated propagation of α-synuclein is associated with early loss of dopamine transporter (DAT) signal in the striatum and loss of dopaminergic neurons in substantia nigra pars compacta of TLR4 deficient mice. These new results support TLR4 signaling as a putative target for disease modification to slow the progression of PD and related disorders."}],"citation":{"short":"S. Venezia, W. Kaufmann, G.K. Wenning, N. Stefanova, Parkinsonism &#38; Related Disorders 91 (2021) 59–65.","apa":"Venezia, S., Kaufmann, W., Wenning, G. K., &#38; Stefanova, N. (2021). Toll-like receptor 4 deficiency facilitates α-synuclein propagation and neurodegeneration in a mouse model of prodromal Parkinson’s disease. <i>Parkinsonism &#38; Related Disorders</i>. Elsevier. <a href=\"https://doi.org/10.1016/j.parkreldis.2021.09.007\">https://doi.org/10.1016/j.parkreldis.2021.09.007</a>","chicago":"Venezia, Serena, Walter Kaufmann, Gregor K. Wenning, and Nadia Stefanova. “Toll-like Receptor 4 Deficiency Facilitates α-Synuclein Propagation and Neurodegeneration in a Mouse Model of Prodromal Parkinson’s Disease.” <i>Parkinsonism &#38; Related Disorders</i>. Elsevier, 2021. <a href=\"https://doi.org/10.1016/j.parkreldis.2021.09.007\">https://doi.org/10.1016/j.parkreldis.2021.09.007</a>.","mla":"Venezia, Serena, et al. “Toll-like Receptor 4 Deficiency Facilitates α-Synuclein Propagation and Neurodegeneration in a Mouse Model of Prodromal Parkinson’s Disease.” <i>Parkinsonism &#38; Related Disorders</i>, vol. 91, Elsevier, 2021, pp. 59–65, doi:<a href=\"https://doi.org/10.1016/j.parkreldis.2021.09.007\">10.1016/j.parkreldis.2021.09.007</a>.","ieee":"S. Venezia, W. Kaufmann, G. K. Wenning, and N. Stefanova, “Toll-like receptor 4 deficiency facilitates α-synuclein propagation and neurodegeneration in a mouse model of prodromal Parkinson’s disease,” <i>Parkinsonism &#38; Related Disorders</i>, vol. 91. Elsevier, pp. 59–65, 2021.","ista":"Venezia S, Kaufmann W, Wenning GK, Stefanova N. 2021. Toll-like receptor 4 deficiency facilitates α-synuclein propagation and neurodegeneration in a mouse model of prodromal Parkinson’s disease. Parkinsonism &#38; Related Disorders. 91, 59–65.","ama":"Venezia S, Kaufmann W, Wenning GK, Stefanova N. Toll-like receptor 4 deficiency facilitates α-synuclein propagation and neurodegeneration in a mouse model of prodromal Parkinson’s disease. <i>Parkinsonism &#38; Related Disorders</i>. 2021;91:59-65. doi:<a href=\"https://doi.org/10.1016/j.parkreldis.2021.09.007\">10.1016/j.parkreldis.2021.09.007</a>"},"year":"2021","oa_version":"Published Version","article_processing_charge":"No","file_date_updated":"2022-01-10T13:41:40Z","publication_status":"published","title":"Toll-like receptor 4 deficiency facilitates α-synuclein propagation and neurodegeneration in a mouse model of prodromal Parkinson's disease","acknowledgement":"This study was supported by grants of the Austrian Science Fund (FWF) F4414 and W1206-08. Electron microscopy was performed at the Scientific Service Units (SSU) of IST-Austria through resources provided by the Electron Microscopy Facility.","publication_identifier":{"eissn":["1873-5126"],"issn":["1353-8020"]},"article_type":"original","scopus_import":"1","doi":"10.1016/j.parkreldis.2021.09.007","date_updated":"2023-08-17T06:36:01Z","publication":"Parkinsonism & Related Disorders","department":[{"_id":"EM-Fac"}],"intvolume":"        91","volume":91,"oa":1,"user_id":"4359f0d1-fa6c-11eb-b949-802e58b17ae8","author":[{"last_name":"Venezia","first_name":"Serena","full_name":"Venezia, Serena"},{"full_name":"Kaufmann, Walter","id":"3F99E422-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0001-9735-5315","last_name":"Kaufmann","first_name":"Walter"},{"full_name":"Wenning, Gregor K.","first_name":"Gregor K.","last_name":"Wenning"},{"last_name":"Stefanova","first_name":"Nadia","full_name":"Stefanova, Nadia"}],"has_accepted_license":"1","tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","image":"/images/cc_by.png","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","short":"CC BY (4.0)"},"quality_controlled":"1","day":"01","page":"59-65","status":"public","isi":1,"month":"10","ddc":["610"],"language":[{"iso":"eng"}],"type":"journal_article","date_published":"2021-10-01T00:00:00Z","external_id":{"isi":["000701142900012"],"pmid":["34530328"]},"pmid":1,"publisher":"Elsevier"},{"type":"journal_article","date_published":"2021-12-30T00:00:00Z","publisher":"Springer Nature","status":"public","month":"12","ddc":["500"],"language":[{"iso":"eng"}],"quality_controlled":"1","day":"30","tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","image":"/images/cc_by.png","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","short":"CC BY (4.0)"},"has_accepted_license":"1","oa":1,"user_id":"8b945eb4-e2f2-11eb-945a-df72226e66a9","author":[{"full_name":"Weighill, Thomas","first_name":"Thomas","last_name":"Weighill"},{"last_name":"Yamauchi","first_name":"Takamitsu","full_name":"Yamauchi, Takamitsu"},{"id":"c8b3499c-7a77-11eb-b046-aa368cbbf2ad","full_name":"Zava, Nicolò","first_name":"Nicolò","last_name":"Zava"}],"date_updated":"2022-01-10T08:36:55Z","publication":"European Journal of Mathematics","department":[{"_id":"HeEd"}],"oa_version":"Published Version","article_processing_charge":"Yes (via OA deal)","file_date_updated":"2022-01-10T08:33:22Z","title":"Coarse infinite-dimensionality of hyperspaces of finite subsets","publication_status":"published","acknowledgement":"We would like to thank the referees for their careful reading and the comments that improved our work. The third named author would like to thank the Division of Mathematics, Physics and Earth Sciences of the Graduate School of Science and Engineering of Ehime University and the second named author for hosting his visit in June 2018. Open access funding provided by Institute of Science and Technology (IST Austria).","publication_identifier":{"eissn":["2199-6768"],"issn":["2199-675X"]},"article_type":"original","scopus_import":"1","doi":"10.1007/s40879-021-00515-3","date_created":"2022-01-09T23:01:27Z","file":[{"success":1,"access_level":"open_access","file_name":"2021_EuJournalMath_Weighill.pdf","relation":"main_file","date_created":"2022-01-10T08:33:22Z","date_updated":"2022-01-10T08:33:22Z","file_size":384908,"creator":"cchlebak","file_id":"10610","content_type":"application/pdf","checksum":"c435dcfa1ad3aadc5cdd7366bc7f4e98"}],"_id":"10608","abstract":[{"text":"We consider infinite-dimensional properties in coarse geometry for hyperspaces consisting of finite subsets of metric spaces with the Hausdorff metric. We see that several infinite-dimensional properties are preserved by taking the hyperspace of subsets with at most n points. On the other hand, we prove that, if a metric space contains a sequence of long intervals coarsely, then its hyperspace of finite subsets is not coarsely embeddable into any uniformly convex Banach space. As a corollary, the hyperspace of finite subsets of the real line is not coarsely embeddable into any uniformly convex Banach space. It is also shown that every (not necessarily bounded geometry) metric space with straight finite decomposition complexity has metric sparsification property.","lang":"eng"}],"citation":{"ama":"Weighill T, Yamauchi T, Zava N. Coarse infinite-dimensionality of hyperspaces of finite subsets. <i>European Journal of Mathematics</i>. 2021. doi:<a href=\"https://doi.org/10.1007/s40879-021-00515-3\">10.1007/s40879-021-00515-3</a>","ieee":"T. Weighill, T. Yamauchi, and N. Zava, “Coarse infinite-dimensionality of hyperspaces of finite subsets,” <i>European Journal of Mathematics</i>. Springer Nature, 2021.","ista":"Weighill T, Yamauchi T, Zava N. 2021. Coarse infinite-dimensionality of hyperspaces of finite subsets. European Journal of Mathematics.","mla":"Weighill, Thomas, et al. “Coarse Infinite-Dimensionality of Hyperspaces of Finite Subsets.” <i>European Journal of Mathematics</i>, Springer Nature, 2021, doi:<a href=\"https://doi.org/10.1007/s40879-021-00515-3\">10.1007/s40879-021-00515-3</a>.","chicago":"Weighill, Thomas, Takamitsu Yamauchi, and Nicolò Zava. “Coarse Infinite-Dimensionality of Hyperspaces of Finite Subsets.” <i>European Journal of Mathematics</i>. Springer Nature, 2021. <a href=\"https://doi.org/10.1007/s40879-021-00515-3\">https://doi.org/10.1007/s40879-021-00515-3</a>.","short":"T. Weighill, T. Yamauchi, N. Zava, European Journal of Mathematics (2021).","apa":"Weighill, T., Yamauchi, T., &#38; Zava, N. (2021). Coarse infinite-dimensionality of hyperspaces of finite subsets. <i>European Journal of Mathematics</i>. Springer Nature. <a href=\"https://doi.org/10.1007/s40879-021-00515-3\">https://doi.org/10.1007/s40879-021-00515-3</a>"},"year":"2021"},{"project":[{"grant_number":"682815","call_identifier":"H2020","name":"Teaching Old Crypto New Tricks","_id":"258AA5B2-B435-11E9-9278-68D0E5697425"}],"page":"335-364","day":"01","quality_controlled":"1","language":[{"iso":"eng"}],"alternative_title":["LNCS"],"isi":1,"month":"12","status":"public","publisher":"Springer Nature","type":"conference","date_published":"2021-12-01T00:00:00Z","external_id":{"isi":["000927876200012"]},"citation":{"short":"S. Chakraborty, C. Ganesh, M. Pancholi, P. Sarkar, in:, 27th International Conference on the Theory and Application of Cryptology and Information Security, Springer Nature, 2021, pp. 335–364.","apa":"Chakraborty, S., Ganesh, C., Pancholi, M., &#38; Sarkar, P. (2021). Reverse firewalls for adaptively secure MPC without setup. In <i>27th International Conference on the Theory and Application of Cryptology and Information Security</i> (Vol. 13091, pp. 335–364). Virtual, Singapore: Springer Nature. <a href=\"https://doi.org/10.1007/978-3-030-92075-3_12\">https://doi.org/10.1007/978-3-030-92075-3_12</a>","chicago":"Chakraborty, Suvradip, Chaya Ganesh, Mahak Pancholi, and Pratik Sarkar. “Reverse Firewalls for Adaptively Secure MPC without Setup.” In <i>27th International Conference on the Theory and Application of Cryptology and Information Security</i>, 13091:335–64. Springer Nature, 2021. <a href=\"https://doi.org/10.1007/978-3-030-92075-3_12\">https://doi.org/10.1007/978-3-030-92075-3_12</a>.","mla":"Chakraborty, Suvradip, et al. “Reverse Firewalls for Adaptively Secure MPC without Setup.” <i>27th International Conference on the Theory and Application of Cryptology and Information Security</i>, vol. 13091, Springer Nature, 2021, pp. 335–64, doi:<a href=\"https://doi.org/10.1007/978-3-030-92075-3_12\">10.1007/978-3-030-92075-3_12</a>.","ama":"Chakraborty S, Ganesh C, Pancholi M, Sarkar P. Reverse firewalls for adaptively secure MPC without setup. In: <i>27th International Conference on the Theory and Application of Cryptology and Information Security</i>. Vol 13091. Springer Nature; 2021:335-364. doi:<a href=\"https://doi.org/10.1007/978-3-030-92075-3_12\">10.1007/978-3-030-92075-3_12</a>","ista":"Chakraborty S, Ganesh C, Pancholi M, Sarkar P. 2021. Reverse firewalls for adaptively secure MPC without setup. 27th International Conference on the Theory and Application of Cryptology and Information Security. ASIACRYPT: International Conference on Cryptology in Asia, LNCS, vol. 13091, 335–364.","ieee":"S. Chakraborty, C. Ganesh, M. Pancholi, and P. Sarkar, “Reverse firewalls for adaptively secure MPC without setup,” in <i>27th International Conference on the Theory and Application of Cryptology and Information Security</i>, Virtual, Singapore, 2021, vol. 13091, pp. 335–364."},"year":"2021","abstract":[{"lang":"eng","text":"We study Multi-party computation (MPC) in the setting of subversion, where the adversary tampers with the machines of honest parties. Our goal is to construct actively secure MPC protocols where parties are corrupted adaptively by an adversary (as in the standard adaptive security setting), and in addition, honest parties’ machines are compromised.\r\nThe idea of reverse firewalls (RF) was introduced at EUROCRYPT’15 by Mironov and Stephens-Davidowitz as an approach to protecting protocols against corruption of honest parties’ devices. Intuitively, an RF for a party   P  is an external entity that sits between   P  and the outside world and whose scope is to sanitize   P ’s incoming and outgoing messages in the face of subversion of their computer. Mironov and Stephens-Davidowitz constructed a protocol for passively-secure two-party computation. At CRYPTO’20, Chakraborty, Dziembowski and Nielsen constructed a protocol for secure computation with firewalls that improved on this result, both by extending it to multi-party computation protocol, and considering active security in the presence of static corruptions. In this paper, we initiate the study of RF for MPC in the adaptive setting. We put forward a definition for adaptively secure MPC in the reverse firewall setting, explore relationships among the security notions, and then construct reverse firewalls for MPC in this stronger setting of adaptive security. We also resolve the open question of Chakraborty, Dziembowski and Nielsen by removing the need for a trusted setup in constructing RF for MPC. Towards this end, we construct reverse firewalls for adaptively secure augmented coin tossing and adaptively secure zero-knowledge protocols and obtain a constant round adaptively secure MPC protocol in the reverse firewall setting without setup. Along the way, we propose a new multi-party adaptively secure coin tossing protocol in the plain model, that is of independent interest."}],"conference":{"start_date":"2021-12-06","name":"ASIACRYPT: International Conference on Cryptology in Asia","location":"Virtual, Singapore","end_date":"2021-12-10"},"date_created":"2022-01-09T23:01:27Z","_id":"10609","scopus_import":"1","doi":"10.1007/978-3-030-92075-3_12","main_file_link":[{"open_access":"1","url":"https://eprint.iacr.org/2021/1262"}],"publication_identifier":{"issn":["0302-9743"],"isbn":["978-3-030-92074-6"],"eisbn":["978-3-030-92075-3"],"eissn":["1611-3349"]},"publication_status":"published","title":"Reverse firewalls for adaptively secure MPC without setup","article_processing_charge":"No","oa_version":"Preprint","intvolume":"     13091","department":[{"_id":"KrPi"}],"date_updated":"2023-08-17T06:34:41Z","ec_funded":1,"publication":"27th International Conference on the Theory and Application of Cryptology and Information Security","author":[{"full_name":"Chakraborty, Suvradip","id":"B9CD0494-D033-11E9-B219-A439E6697425","last_name":"Chakraborty","first_name":"Suvradip"},{"full_name":"Ganesh, Chaya","first_name":"Chaya","last_name":"Ganesh"},{"full_name":"Pancholi, Mahak","last_name":"Pancholi","first_name":"Mahak"},{"last_name":"Sarkar","first_name":"Pratik","full_name":"Sarkar, Pratik"}],"user_id":"4359f0d1-fa6c-11eb-b949-802e58b17ae8","volume":13091,"oa":1},{"ec_funded":1,"date_updated":"2022-01-10T15:29:08Z","publication":"Markov Processes And Related Fields","department":[{"_id":"JaMa"}],"intvolume":"        27","arxiv":1,"volume":27,"related_material":{"link":[{"url":"http://math-mprf.org/journal/articles/id1614/","description":"Link to Abstract on publisher's website","relation":"other"},{"description":"Referred to in Abstract","relation":"used_for_analysis_in","url":"https://arxiv.org/abs/2004.08412"}]},"oa":1,"user_id":"8b945eb4-e2f2-11eb-945a-df72226e66a9","author":[{"full_name":"Chen, Joe P.","last_name":"Chen","first_name":"Joe P."},{"id":"E1836206-9F16-11E9-8814-AEFDE5697425","full_name":"Sau, Federico","first_name":"Federico","last_name":"Sau"}],"date_created":"2022-01-10T14:02:31Z","_id":"10613","abstract":[{"lang":"eng","text":"Motivated by the recent preprint [\\emph{arXiv:2004.08412}] by Ayala, Carinci, and Redig, we first provide a general framework for the study of scaling limits of higher-order fields. Then, by considering the same class of infinite interacting particle systems as in [\\emph{arXiv:2004.08412}], namely symmetric simple exclusion and inclusion processes in the d-dimensional Euclidean lattice, we prove the hydrodynamic limit, and convergence for the equilibrium fluctuations, of higher-order fields. In particular, the limit fields exhibit a tensor structure. Our fluctuation result differs from that in [\\emph{arXiv:2004.08412}], since we considered-dimensional Euclidean lattice, we prove the hydrodynamic limit, and convergence for the equilibrium fluctuations, of higher-order fields. In particular, the limit fields exhibit a tensor structure. Our fluctuation result differs from that in [\\emph{arXiv:2004.08412}], since we consider a different notion of higher-order fluctuation fields."}],"citation":{"mla":"Chen, Joe P., and Federico Sau. “Higher-Order Hydrodynamics and Equilibrium Fluctuations of Interacting Particle Systems.” <i>Markov Processes And Related Fields</i>, vol. 27, no. 3, Polymat Publishing, 2021, pp. 339–80.","short":"J.P. Chen, F. Sau, Markov Processes And Related Fields 27 (2021) 339–380.","apa":"Chen, J. P., &#38; Sau, F. (2021). Higher-order hydrodynamics and equilibrium fluctuations of interacting particle systems. <i>Markov Processes And Related Fields</i>. Polymat Publishing.","chicago":"Chen, Joe P., and Federico Sau. “Higher-Order Hydrodynamics and Equilibrium Fluctuations of Interacting Particle Systems.” <i>Markov Processes And Related Fields</i>. Polymat Publishing, 2021.","ama":"Chen JP, Sau F. Higher-order hydrodynamics and equilibrium fluctuations of interacting particle systems. <i>Markov Processes And Related Fields</i>. 2021;27(3):339-380.","ista":"Chen JP, Sau F. 2021. Higher-order hydrodynamics and equilibrium fluctuations of interacting particle systems. Markov Processes And Related Fields. 27(3), 339–380.","ieee":"J. P. Chen and F. Sau, “Higher-order hydrodynamics and equilibrium fluctuations of interacting particle systems,” <i>Markov Processes And Related Fields</i>, vol. 27, no. 3. Polymat Publishing, pp. 339–380, 2021."},"year":"2021","article_processing_charge":"No","oa_version":"Preprint","title":"Higher-order hydrodynamics and equilibrium fluctuations of interacting particle systems","publication_status":"published","acknowledgement":"F.S. would like to thank Mario Ayala and Frank Redig for useful discussions. J.P.C. acknowledges partial financial support from the US National Science Foundation (DMS-1855604). F.S. was financially supported by the European Union’s Horizon 2020 research and innovation programme under the Marie-Skłodowska-Curie grant agreement No. 754411.\r\n","publication_identifier":{"issn":["1024-2953"]},"article_type":"original","main_file_link":[{"url":"https://arxiv.org/abs/2008.13403","open_access":"1"}],"status":"public","month":"03","keyword":["interacting particle systems","higher-order fields","hydrodynamic limit","equilibrium fluctuations","duality"],"language":[{"iso":"eng"}],"type":"journal_article","date_published":"2021-03-16T00:00:00Z","external_id":{"arxiv":["2008.13403"]},"publisher":"Polymat Publishing","project":[{"_id":"260C2330-B435-11E9-9278-68D0E5697425","name":"ISTplus - Postdoctoral Fellowships","call_identifier":"H2020","grant_number":"754411"}],"issue":"3","quality_controlled":"1","day":"16","page":"339-380"},{"ec_funded":1,"date_updated":"2023-08-17T06:54:54Z","publication":"New Journal of Physics","department":[{"_id":"MiLe"}],"intvolume":"        23","arxiv":1,"volume":23,"oa":1,"user_id":"4359f0d1-fa6c-11eb-b949-802e58b17ae8","author":[{"last_name":"Ghazaryan","first_name":"Areg","full_name":"Ghazaryan, Areg","id":"4AF46FD6-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0001-9666-3543"},{"last_name":"Nica","first_name":"Emilian M.","full_name":"Nica, Emilian M."},{"full_name":"Erten, Onur","first_name":"Onur","last_name":"Erten"},{"full_name":"Ghaemi, Pouyan","first_name":"Pouyan","last_name":"Ghaemi"}],"file":[{"content_type":"application/pdf","creator":"cchlebak","file_id":"10632","checksum":"0c3cb6816242fa8afd1cc87a5fe77821","success":1,"access_level":"open_access","file_name":"2021_NewJourPhys_Ghazaryan.pdf","file_size":2533102,"relation":"main_file","date_created":"2022-01-17T10:01:58Z","date_updated":"2022-01-17T10:01:58Z"}],"date_created":"2022-01-16T23:01:28Z","_id":"10628","abstract":[{"lang":"eng","text":"The surface states of 3D topological insulators in general have negligible quantum oscillations (QOs) when the chemical potential is tuned to the Dirac points. In contrast, we find that topological Kondo insulators (TKIs) can support surface states with an arbitrarily large Fermi surface (FS) when the chemical potential is pinned to the Dirac point. We illustrate that these FSs give rise to finite-frequency QOs, which can become comparable to the extremal area of the unhybridized bulk bands. We show that this occurs when the crystal symmetry is lowered from cubic to tetragonal in a minimal two-orbital model. We label such surface modes as 'shadow surface states'. Moreover, we show that the sufficient next-nearest neighbor out-of-plane hybridization leading to shadow surface states can be self-consistently stabilized for tetragonal TKIs. Consequently, shadow surface states provide an important example of high-frequency QOs beyond the context of cubic TKIs."}],"citation":{"ama":"Ghazaryan A, Nica EM, Erten O, Ghaemi P. Shadow surface states in topological Kondo insulators. <i>New Journal of Physics</i>. 2021;23(12). doi:<a href=\"https://doi.org/10.1088/1367-2630/ac4124\">10.1088/1367-2630/ac4124</a>","ieee":"A. Ghazaryan, E. M. Nica, O. Erten, and P. Ghaemi, “Shadow surface states in topological Kondo insulators,” <i>New Journal of Physics</i>, vol. 23, no. 12. IOP Publishing, 2021.","ista":"Ghazaryan A, Nica EM, Erten O, Ghaemi P. 2021. Shadow surface states in topological Kondo insulators. New Journal of Physics. 23(12), 123042.","apa":"Ghazaryan, A., Nica, E. M., Erten, O., &#38; Ghaemi, P. (2021). Shadow surface states in topological Kondo insulators. <i>New Journal of Physics</i>. IOP Publishing. <a href=\"https://doi.org/10.1088/1367-2630/ac4124\">https://doi.org/10.1088/1367-2630/ac4124</a>","short":"A. Ghazaryan, E.M. Nica, O. Erten, P. Ghaemi, New Journal of Physics 23 (2021).","chicago":"Ghazaryan, Areg, Emilian M. Nica, Onur Erten, and Pouyan Ghaemi. “Shadow Surface States in Topological Kondo Insulators.” <i>New Journal of Physics</i>. IOP Publishing, 2021. <a href=\"https://doi.org/10.1088/1367-2630/ac4124\">https://doi.org/10.1088/1367-2630/ac4124</a>.","mla":"Ghazaryan, Areg, et al. “Shadow Surface States in Topological Kondo Insulators.” <i>New Journal of Physics</i>, vol. 23, no. 12, 123042, IOP Publishing, 2021, doi:<a href=\"https://doi.org/10.1088/1367-2630/ac4124\">10.1088/1367-2630/ac4124</a>."},"article_number":"123042","year":"2021","article_processing_charge":"No","oa_version":"Published Version","file_date_updated":"2022-01-17T10:01:58Z","title":"Shadow surface states in topological Kondo insulators","publication_status":"published","acknowledgement":"PG acknowledges support from National Science Foundation Awards No. DMR-1824265 for this work. AG acknowledges support from the European Union's Horizon 2020 research and innovation program under the Marie Skłodowska-Curie Grant Agreement No. 754411. EMN is supported by ASU startup grant. OE is in part supported by NSF-DMR-1904716.","publication_identifier":{"issn":["1367-2630"]},"article_type":"original","scopus_import":"1","doi":"10.1088/1367-2630/ac4124","status":"public","isi":1,"month":"12","ddc":["530"],"language":[{"iso":"eng"}],"type":"journal_article","date_published":"2021-12-23T00:00:00Z","external_id":{"arxiv":["2012.11625"],"isi":["000734063700001"]},"publisher":"IOP Publishing","tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","image":"/images/cc_by.png","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","short":"CC BY (4.0)"},"has_accepted_license":"1","project":[{"call_identifier":"H2020","grant_number":"754411","name":"ISTplus - Postdoctoral Fellowships","_id":"260C2330-B435-11E9-9278-68D0E5697425"}],"issue":"12","quality_controlled":"1","day":"23"},{"quality_controlled":"1","day":"29","tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","image":"/images/cc_by.png","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","short":"CC BY (4.0)"},"has_accepted_license":"1","type":"conference","date_published":"2021-11-29T00:00:00Z","publisher":"Schloss Dagstuhl - Leibniz-Zentrum für Informatik","month":"11","status":"public","ddc":["000"],"language":[{"iso":"eng"}],"alternative_title":["LIPIcs"],"title":"Quantitative verification on product graphs of small treewidth","publication_status":"published","oa_version":"Published Version","article_processing_charge":"No","file_date_updated":"2022-01-17T10:36:08Z","scopus_import":"1","doi":"10.4230/LIPIcs.FSTTCS.2021.42","publication_identifier":{"isbn":["978-3-9597-7215-0"],"issn":["1868-8969"]},"conference":{"start_date":"2021-12-15","name":"FSTTCS: Foundations of Software Technology and Theoretical Computer Science","location":"Virtual","end_date":"2021-12-17"},"date_created":"2022-01-16T23:01:28Z","file":[{"file_name":"2021_LIPIcs_Chatterjee.pdf","success":1,"access_level":"open_access","file_size":891566,"relation":"main_file","date_created":"2022-01-17T10:36:08Z","date_updated":"2022-01-17T10:36:08Z","content_type":"application/pdf","file_id":"10633","creator":"cchlebak","checksum":"71141acdeffa9056f24d6dbef952d254"}],"_id":"10629","citation":{"chicago":"Chatterjee, Krishnendu, Rasmus Ibsen-Jensen, and Andreas Pavlogiannis. “Quantitative Verification on Product Graphs of Small Treewidth.” In <i>41st IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science</i>, Vol. 213. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2021. <a href=\"https://doi.org/10.4230/LIPIcs.FSTTCS.2021.42\">https://doi.org/10.4230/LIPIcs.FSTTCS.2021.42</a>.","short":"K. Chatterjee, R. Ibsen-Jensen, A. Pavlogiannis, in:, 41st IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2021.","apa":"Chatterjee, K., Ibsen-Jensen, R., &#38; Pavlogiannis, A. (2021). Quantitative verification on product graphs of small treewidth. In <i>41st IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science</i> (Vol. 213). Virtual: Schloss Dagstuhl - Leibniz-Zentrum für Informatik. <a href=\"https://doi.org/10.4230/LIPIcs.FSTTCS.2021.42\">https://doi.org/10.4230/LIPIcs.FSTTCS.2021.42</a>","mla":"Chatterjee, Krishnendu, et al. “Quantitative Verification on Product Graphs of Small Treewidth.” <i>41st IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science</i>, vol. 213, 42, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2021, doi:<a href=\"https://doi.org/10.4230/LIPIcs.FSTTCS.2021.42\">10.4230/LIPIcs.FSTTCS.2021.42</a>.","ista":"Chatterjee K, Ibsen-Jensen R, Pavlogiannis A. 2021. Quantitative verification on product graphs of small treewidth. 41st IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science. FSTTCS: Foundations of Software Technology and Theoretical Computer Science, LIPIcs, vol. 213, 42.","ieee":"K. Chatterjee, R. Ibsen-Jensen, and A. Pavlogiannis, “Quantitative verification on product graphs of small treewidth,” in <i>41st IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science</i>, Virtual, 2021, vol. 213.","ama":"Chatterjee K, Ibsen-Jensen R, Pavlogiannis A. Quantitative verification on product graphs of small treewidth. In: <i>41st IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science</i>. Vol 213. Schloss Dagstuhl - Leibniz-Zentrum für Informatik; 2021. doi:<a href=\"https://doi.org/10.4230/LIPIcs.FSTTCS.2021.42\">10.4230/LIPIcs.FSTTCS.2021.42</a>"},"article_number":"42","year":"2021","abstract":[{"lang":"eng","text":"Product graphs arise naturally in formal verification and program analysis. For example, the analysis of two concurrent threads requires the product of two component control-flow graphs, and for language inclusion of deterministic automata the product of two automata is constructed. In many cases, the component graphs have constant treewidth, e.g., when the input contains control-flow graphs of programs. We consider the algorithmic analysis of products of two constant-treewidth graphs with respect to three classic specification languages, namely, (a) algebraic properties, (b) mean-payoff properties, and (c) initial credit for energy properties.\r\nOur main contributions are as follows. Consider a graph G that is the product of two constant-treewidth graphs of size n each. First, given an idempotent semiring, we present an algorithm that computes the semiring transitive closure of G in time Õ(n⁴). Since the output has size Θ(n⁴), our algorithm is optimal (up to polylog factors). Second, given a mean-payoff objective, we present an O(n³)-time algorithm for deciding whether the value of a starting state is non-negative, improving the previously known O(n⁴) bound. Third, given an initial credit for energy objective, we present an O(n⁵)-time algorithm for computing the minimum initial credit for all nodes of G, improving the previously known O(n⁸) bound. At the heart of our approach lies an algorithm for the efficient construction of strongly-balanced tree decompositions of constant-treewidth graphs. Given a constant-treewidth graph G' of n nodes and a positive integer λ, our algorithm constructs a binary tree decomposition of G' of width O(λ) with the property that the size of each subtree decreases geometrically with rate (1/2 + 2^{-λ})."}],"volume":213,"oa":1,"author":[{"id":"2E5DCA20-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-4561-241X","full_name":"Chatterjee, Krishnendu","first_name":"Krishnendu","last_name":"Chatterjee"},{"full_name":"Ibsen-Jensen, Rasmus","id":"3B699956-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0003-4783-0389","last_name":"Ibsen-Jensen","first_name":"Rasmus"},{"orcid":"0000-0002-8943-0722","id":"49704004-F248-11E8-B48F-1D18A9856A87","full_name":"Pavlogiannis, Andreas","first_name":"Andreas","last_name":"Pavlogiannis"}],"user_id":"8b945eb4-e2f2-11eb-945a-df72226e66a9","department":[{"_id":"KrCh"}],"date_updated":"2022-01-17T10:39:40Z","publication":"41st IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science","intvolume":"       213"},{"has_accepted_license":"1","tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","image":"/images/cc_by.png","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","short":"CC BY (4.0)"},"project":[{"name":"ISTplus - Postdoctoral Fellowships","_id":"260C2330-B435-11E9-9278-68D0E5697425","grant_number":"754411","call_identifier":"H2020"}],"day":"29","quality_controlled":"1","alternative_title":["LIPIcs"],"ddc":["000"],"language":[{"iso":"eng"}],"status":"public","month":"11","publisher":"Schloss Dagstuhl - Leibniz Zentrum für Informatik","type":"conference","external_id":{"arxiv":["2110.01279"]},"date_published":"2021-11-29T00:00:00Z","abstract":[{"lang":"eng","text":"In the Intersection Non-emptiness problem, we are given a list of finite automata A_1, A_2,… , A_m over a common alphabet Σ as input, and the goal is to determine whether some string w ∈ Σ^* lies in the intersection of the languages accepted by the automata in the list. We analyze the complexity of the Intersection Non-emptiness problem under the promise that all input automata accept a language in some level of the dot-depth hierarchy, or some level of the Straubing-Thérien hierarchy. Automata accepting languages from the lowest levels of these hierarchies arise naturally in the context of model checking. We identify a dichotomy in the dot-depth hierarchy by showing that the problem is already NP-complete when all input automata accept languages of the levels B_0 or B_{1/2} and already PSPACE-hard when all automata accept a language from the level B_1. Conversely, we identify a tetrachotomy in the Straubing-Thérien hierarchy. More precisely, we show that the problem is in AC^0 when restricted to level L_0; complete for L or NL, depending on the input representation, when restricted to languages in the level L_{1/2}; NP-complete when the input is given as DFAs accepting a language in L_1 or L_{3/2}; and finally, PSPACE-complete when the input automata accept languages in level L_2 or higher. Moreover, we show that the proof technique used to show containment in NP for DFAs accepting languages in L_1 or L_{3/2} does not generalize to the context of NFAs. To prove this, we identify a family of languages that provide an exponential separation between the state complexity of general NFAs and that of partially ordered NFAs. To the best of our knowledge, this is the first superpolynomial separation between these two models of computation."}],"citation":{"ama":"Arrighi E, Fernau H, Hoffmann S, et al. On the complexity of intersection non-emptiness for star-free language classes. In: <i>41st IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science</i>. Vol 213. Schloss Dagstuhl - Leibniz Zentrum für Informatik; 2021. doi:<a href=\"https://doi.org/10.4230/LIPIcs.FSTTCS.2021.34\">10.4230/LIPIcs.FSTTCS.2021.34</a>","ista":"Arrighi E, Fernau H, Hoffmann S, Holzer M, Jecker IR, De Oliveira Oliveira M, Wolf P. 2021. On the complexity of intersection non-emptiness for star-free language classes. 41st IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science. FSTTCS: Foundations of Software Technology and Theoretical Computer Science, LIPIcs, vol. 213, 34.","ieee":"E. Arrighi <i>et al.</i>, “On the complexity of intersection non-emptiness for star-free language classes,” in <i>41st IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science</i>, Virtual, 2021, vol. 213.","mla":"Arrighi, Emmanuel, et al. “On the Complexity of Intersection Non-Emptiness for Star-Free Language Classes.” <i>41st IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science</i>, vol. 213, 34, Schloss Dagstuhl - Leibniz Zentrum für Informatik, 2021, doi:<a href=\"https://doi.org/10.4230/LIPIcs.FSTTCS.2021.34\">10.4230/LIPIcs.FSTTCS.2021.34</a>.","short":"E. Arrighi, H. Fernau, S. Hoffmann, M. Holzer, I.R. Jecker, M. De Oliveira Oliveira, P. Wolf, in:, 41st IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science, Schloss Dagstuhl - Leibniz Zentrum für Informatik, 2021.","chicago":"Arrighi, Emmanuel, Henning Fernau, Stefan Hoffmann, Markus Holzer, Ismael R Jecker, Mateus De Oliveira Oliveira, and Petra Wolf. “On the Complexity of Intersection Non-Emptiness for Star-Free Language Classes.” In <i>41st IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science</i>, Vol. 213. Schloss Dagstuhl - Leibniz Zentrum für Informatik, 2021. <a href=\"https://doi.org/10.4230/LIPIcs.FSTTCS.2021.34\">https://doi.org/10.4230/LIPIcs.FSTTCS.2021.34</a>.","apa":"Arrighi, E., Fernau, H., Hoffmann, S., Holzer, M., Jecker, I. R., De Oliveira Oliveira, M., &#38; Wolf, P. (2021). On the complexity of intersection non-emptiness for star-free language classes. In <i>41st IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science</i> (Vol. 213). Virtual: Schloss Dagstuhl - Leibniz Zentrum für Informatik. <a href=\"https://doi.org/10.4230/LIPIcs.FSTTCS.2021.34\">https://doi.org/10.4230/LIPIcs.FSTTCS.2021.34</a>"},"year":"2021","article_number":"34","date_created":"2022-01-16T23:01:29Z","file":[{"checksum":"d5a82ba893c3bc5da5914edbb3efb92b","file_id":"10634","creator":"cchlebak","content_type":"application/pdf","file_size":844224,"date_updated":"2022-01-17T10:49:03Z","relation":"main_file","date_created":"2022-01-17T10:49:03Z","success":1,"access_level":"open_access","file_name":"2021_LIPIcs_Arrighi.pdf"}],"_id":"10630","conference":{"location":"Virtual","name":"FSTTCS: Foundations of Software Technology and Theoretical Computer Science","end_date":"2021-12-17","start_date":"2021-12-15"},"acknowledgement":"We like to thank Lukas Fleischer and Michael Wehar for our discussions. This work started at the Schloss Dagstuhl Event 20483 Moderne Aspekte der Komplexitätstheorie in der Automatentheorie https://www.dagstuhl.de/20483.\r\n","publication_identifier":{"issn":["1868-8969"],"isbn":["978-3-9597-7215-0"]},"scopus_import":"1","doi":"10.4230/LIPIcs.FSTTCS.2021.34","article_processing_charge":"No","oa_version":"Published Version","file_date_updated":"2022-01-17T10:49:03Z","title":"On the complexity of intersection non-emptiness for star-free language classes","publication_status":"published","intvolume":"       213","arxiv":1,"date_updated":"2022-01-17T10:56:19Z","ec_funded":1,"publication":"41st IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science","department":[{"_id":"KrCh"}],"user_id":"8b945eb4-e2f2-11eb-945a-df72226e66a9","author":[{"full_name":"Arrighi, Emmanuel","first_name":"Emmanuel","last_name":"Arrighi"},{"full_name":"Fernau, Henning","first_name":"Henning","last_name":"Fernau"},{"last_name":"Hoffmann","first_name":"Stefan","full_name":"Hoffmann, Stefan"},{"last_name":"Holzer","first_name":"Markus","full_name":"Holzer, Markus"},{"full_name":"Jecker, Ismael R","id":"85D7C63E-7D5D-11E9-9C0F-98C4E5697425","last_name":"Jecker","first_name":"Ismael R"},{"first_name":"Mateus","last_name":"De Oliveira Oliveira","full_name":"De Oliveira Oliveira, Mateus"},{"last_name":"Wolf","first_name":"Petra","full_name":"Wolf, Petra"}],"volume":213,"oa":1},{"author":[{"last_name":"Cherepanov","first_name":"Igor","full_name":"Cherepanov, Igor","id":"339C7E5A-F248-11E8-B48F-1D18A9856A87"},{"last_name":"Bighin","first_name":"Giacomo","full_name":"Bighin, Giacomo","orcid":"0000-0001-8823-9777","id":"4CA96FD4-F248-11E8-B48F-1D18A9856A87"},{"first_name":"Constant A.","last_name":"Schouder","full_name":"Schouder, Constant A."},{"first_name":"Adam S.","last_name":"Chatterley","full_name":"Chatterley, Adam S."},{"full_name":"Albrechtsen, Simon H.","first_name":"Simon H.","last_name":"Albrechtsen"},{"full_name":"Muñoz, Alberto Viñas","first_name":"Alberto Viñas","last_name":"Muñoz"},{"full_name":"Christiansen, Lars","first_name":"Lars","last_name":"Christiansen"},{"full_name":"Stapelfeldt, Henrik","first_name":"Henrik","last_name":"Stapelfeldt"},{"first_name":"Mikhail","last_name":"Lemeshko","id":"37CB05FA-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-6990-7802","full_name":"Lemeshko, Mikhail"}],"user_id":"4359f0d1-fa6c-11eb-b949-802e58b17ae8","volume":104,"oa":1,"arxiv":1,"intvolume":"       104","department":[{"_id":"MiLe"}],"ec_funded":1,"date_updated":"2024-08-07T07:16:52Z","publication":"Physical Review A","scopus_import":"1","doi":"10.1103/PhysRevA.104.L061303","main_file_link":[{"open_access":"1","url":"http://128.84.4.18/abs/2107.00468"}],"acknowledgement":"I.C. acknowledges the support by the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie Grant Agreement No. 665385. G.B. acknowledges support from the Austrian Science Fund (FWF), under project No. M2461-N27. M.L. acknowledges support by the Austrian Science Fund (FWF), under project No. P29902-N27, and by the European Research Council (ERC) Starting Grant No. 801770 (ANGULON). H.S acknowledges support from the European Research Council-AdG (Project No. 320459, DropletControl) and from The Villum Foundation through a Villum Investigator grant no. 25886.","publication_identifier":{"eissn":["2469-9934"],"issn":["2469-9926"]},"article_type":"original","title":"Excited rotational states of molecules in a superfluid","publication_status":"published","oa_version":"Preprint","article_processing_charge":"No","citation":{"ieee":"I. Cherepanov <i>et al.</i>, “Excited rotational states of molecules in a superfluid,” <i>Physical Review A</i>, vol. 104, no. 6. American Physical Society, 2021.","ista":"Cherepanov I, Bighin G, Schouder CA, Chatterley AS, Albrechtsen SH, Muñoz AV, Christiansen L, Stapelfeldt H, Lemeshko M. 2021. Excited rotational states of molecules in a superfluid. Physical Review A. 104(6), L061303.","ama":"Cherepanov I, Bighin G, Schouder CA, et al. Excited rotational states of molecules in a superfluid. <i>Physical Review A</i>. 2021;104(6). doi:<a href=\"https://doi.org/10.1103/PhysRevA.104.L061303\">10.1103/PhysRevA.104.L061303</a>","mla":"Cherepanov, Igor, et al. “Excited Rotational States of Molecules in a Superfluid.” <i>Physical Review A</i>, vol. 104, no. 6, L061303, American Physical Society, 2021, doi:<a href=\"https://doi.org/10.1103/PhysRevA.104.L061303\">10.1103/PhysRevA.104.L061303</a>.","short":"I. Cherepanov, G. Bighin, C.A. Schouder, A.S. Chatterley, S.H. Albrechtsen, A.V. Muñoz, L. Christiansen, H. Stapelfeldt, M. Lemeshko, Physical Review A 104 (2021).","chicago":"Cherepanov, Igor, Giacomo Bighin, Constant A. Schouder, Adam S. Chatterley, Simon H. Albrechtsen, Alberto Viñas Muñoz, Lars Christiansen, Henrik Stapelfeldt, and Mikhail Lemeshko. “Excited Rotational States of Molecules in a Superfluid.” <i>Physical Review A</i>. American Physical Society, 2021. <a href=\"https://doi.org/10.1103/PhysRevA.104.L061303\">https://doi.org/10.1103/PhysRevA.104.L061303</a>.","apa":"Cherepanov, I., Bighin, G., Schouder, C. A., Chatterley, A. S., Albrechtsen, S. H., Muñoz, A. V., … Lemeshko, M. (2021). Excited rotational states of molecules in a superfluid. <i>Physical Review A</i>. American Physical Society. <a href=\"https://doi.org/10.1103/PhysRevA.104.L061303\">https://doi.org/10.1103/PhysRevA.104.L061303</a>"},"year":"2021","article_number":"L061303","abstract":[{"lang":"eng","text":"We combine experimental and theoretical approaches to explore excited rotational states of molecules embedded in helium nanodroplets using CS2 and I2 as examples. Laser-induced nonadiabatic molecular alignment is employed to measure spectral lines for rotational states extending beyond those initially populated at the 0.37 K droplet temperature. We construct a simple quantum-mechanical model, based on a linear rotor coupled to a single-mode bosonic bath, to determine the rotational energy structure in its entirety. The calculated and measured spectral lines are in good agreement. We show that the effect of the surrounding superfluid on molecular rotation can be rationalized by a single quantity, the angular momentum, transferred from the molecule to the droplet."}],"date_created":"2022-01-16T23:01:29Z","_id":"10631","publisher":"American Physical Society","type":"journal_article","date_published":"2021-12-30T00:00:00Z","external_id":{"isi":["000739618300001"],"arxiv":["2107.00468"]},"language":[{"iso":"eng"}],"isi":1,"month":"12","status":"public","day":"30","quality_controlled":"1","issue":"6","project":[{"_id":"26031614-B435-11E9-9278-68D0E5697425","name":"Quantum rotations in the presence of a many-body environment","grant_number":"P29902","call_identifier":"FWF"},{"grant_number":"801770","call_identifier":"H2020","_id":"2688CF98-B435-11E9-9278-68D0E5697425","name":"Angulon: physics and applications of a new quasiparticle"},{"name":"International IST Doctoral Program","_id":"2564DBCA-B435-11E9-9278-68D0E5697425","grant_number":"665385","call_identifier":"H2020"},{"call_identifier":"FWF","grant_number":"M02641","_id":"26986C82-B435-11E9-9278-68D0E5697425","name":"A path-integral approach to composite impurities"}]},{"oa":1,"volume":1,"user_id":"8b945eb4-e2f2-11eb-945a-df72226e66a9","author":[{"first_name":"Michele","last_name":"Nardin","orcid":"0000-0001-8849-6570","id":"30BD0376-F248-11E8-B48F-1D18A9856A87","full_name":"Nardin, Michele"},{"last_name":"Phillips","first_name":"James W.","full_name":"Phillips, James W."},{"last_name":"Podlaski","first_name":"William F.","full_name":"Podlaski, William F."},{"full_name":"Keemink, Sander W.","last_name":"Keemink","first_name":"Sander W."}],"publication":"Peer Community Journal","date_updated":"2022-01-17T13:30:01Z","ec_funded":1,"department":[{"_id":"GradSch"},{"_id":"JoCs"}],"intvolume":"         1","arxiv":1,"file_date_updated":"2022-01-17T11:15:26Z","oa_version":"Published Version","article_processing_charge":"No","publication_status":"published","title":"Nonlinear computations in spiking neural networks through multiplicative synapses","article_type":"original","publication_identifier":{"eissn":["2804-3871"]},"acknowledgement":"A preprint version of this article has been peer-reviewed and recommended by Peer Community In Neuroscience (DOI link to the recommendation: https://doi.org/10.24072/pci.cneuro.100003).\r\nWe thank Christian Machens and Nuno Calaim for useful discussions on the project. This report\r\ncame out of a collaboration started at the CAJAL Advanced Neuroscience Training Programme in\r\nComputational Neuroscience in Lisbon, Portugal, during the 2019 summer. The authors would\r\nlike to thank the participants, TAs, lecturers, and organizers of the summer school. SWK was\r\nsupported by the Simons Collaboration on the Global Brain (543009). WFP was supported by\r\nFCT (032077). MN was supported by European Union Horizon 2020 (665385).\r\n","doi":"10.24072/pcjournal.69","_id":"10635","file":[{"checksum":"cd9af6b331918608f2e3d1c7940cbf4f","content_type":"application/pdf","file_id":"10636","creator":"mnardin","date_updated":"2022-01-17T11:15:26Z","relation":"main_file","date_created":"2022-01-17T11:15:26Z","file_size":3311494,"access_level":"open_access","success":1,"file_name":"10_24072_pcjournal_69.pdf"}],"date_created":"2022-01-17T11:12:40Z","abstract":[{"lang":"eng","text":"The brain efficiently performs nonlinear computations through its intricate networks of spiking neurons, but how this is done remains elusive. While nonlinear computations can be implemented successfully in spiking neural networks, this requires supervised training and the resulting connectivity can be hard to interpret. In contrast, the required connectivity for any computation in the form of a linear dynamical system can be directly derived and understood with the spike coding network (SCN) framework. These networks also have biologically realistic activity patterns and are highly robust to cell death. Here we extend the SCN framework to directly implement any polynomial dynamical system, without the need for training. This results in networks requiring a mix of synapse types (fast, slow, and multiplicative), which we term multiplicative spike coding networks (mSCNs). Using mSCNs, we demonstrate how to directly derive the required connectivity for several nonlinear dynamical systems. We also show how to carry out higher-order polynomials with coupled networks that use only pair-wise multiplicative synapses, and provide expected numbers of connections for each synapse type. Overall, our work demonstrates a novel method for implementing nonlinear computations in spiking neural networks, while keeping the attractive features of standard SCNs (robustness, realistic activity patterns, and interpretable connectivity). Finally, we discuss the biological plausibility of our approach, and how the high accuracy and robustness of the approach may be of interest for neuromorphic computing."}],"year":"2021","article_number":"e68","citation":{"ista":"Nardin M, Phillips JW, Podlaski WF, Keemink SW. 2021. Nonlinear computations in spiking neural networks through multiplicative synapses. Peer Community Journal. 1, e68.","ieee":"M. Nardin, J. W. Phillips, W. F. Podlaski, and S. W. Keemink, “Nonlinear computations in spiking neural networks through multiplicative synapses,” <i>Peer Community Journal</i>, vol. 1. Centre Mersenne ; Peer Community In, 2021.","ama":"Nardin M, Phillips JW, Podlaski WF, Keemink SW. Nonlinear computations in spiking neural networks through multiplicative synapses. <i>Peer Community Journal</i>. 2021;1. doi:<a href=\"https://doi.org/10.24072/pcjournal.69\">10.24072/pcjournal.69</a>","mla":"Nardin, Michele, et al. “Nonlinear Computations in Spiking Neural Networks through Multiplicative Synapses.” <i>Peer Community Journal</i>, vol. 1, e68, Centre Mersenne ; Peer Community In, 2021, doi:<a href=\"https://doi.org/10.24072/pcjournal.69\">10.24072/pcjournal.69</a>.","apa":"Nardin, M., Phillips, J. W., Podlaski, W. F., &#38; Keemink, S. W. (2021). Nonlinear computations in spiking neural networks through multiplicative synapses. <i>Peer Community Journal</i>. Centre Mersenne ; Peer Community In. <a href=\"https://doi.org/10.24072/pcjournal.69\">https://doi.org/10.24072/pcjournal.69</a>","short":"M. Nardin, J.W. Phillips, W.F. Podlaski, S.W. Keemink, Peer Community Journal 1 (2021).","chicago":"Nardin, Michele, James W. Phillips, William F. Podlaski, and Sander W. Keemink. “Nonlinear Computations in Spiking Neural Networks through Multiplicative Synapses.” <i>Peer Community Journal</i>. Centre Mersenne ; Peer Community In, 2021. <a href=\"https://doi.org/10.24072/pcjournal.69\">https://doi.org/10.24072/pcjournal.69</a>."},"date_published":"2021-12-15T00:00:00Z","external_id":{"arxiv":["2009.03857"]},"type":"journal_article","publisher":"Centre Mersenne ; Peer Community In","status":"public","month":"12","language":[{"iso":"eng"}],"ddc":["519"],"quality_controlled":"1","day":"15","tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","image":"/images/cc_by.png","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","short":"CC BY (4.0)"},"has_accepted_license":"1","project":[{"call_identifier":"H2020","grant_number":"665385","_id":"2564DBCA-B435-11E9-9278-68D0E5697425","name":"International IST Doctoral Program"}]},{"alternative_title":["Bluefors Blog"],"keyword":["Application note"],"language":[{"iso":"eng"}],"date_updated":"2022-01-19T09:11:33Z","status":"public","department":[{"_id":"JoFi"}],"month":"04","user_id":"8b945eb4-e2f2-11eb-945a-df72226e66a9","author":[{"full_name":"Lake, Russell","last_name":"Lake","first_name":"Russell"},{"first_name":"Slawomir","last_name":"Simbierowicz","full_name":"Simbierowicz, Slawomir"},{"full_name":"Krantz, Philip","last_name":"Krantz","first_name":"Philip"},{"last_name":"Hassani","first_name":"Farid","full_name":"Hassani, Farid","id":"2AED110C-F248-11E8-B48F-1D18A9856A87"},{"first_name":"Johannes M","last_name":"Fink","id":"4B591CBA-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0001-8112-028X","full_name":"Fink, Johannes M"}],"publisher":"Bluefors Oy","oa":1,"type":"other_academic_publication","date_published":"2021-04-20T00:00:00Z","abstract":[{"text":"The purpose of this application note is to demonstrate a working example of a superconducting qubit measurement in a Bluefors cryostat using the Keysight quantum control hardware. Our motivation is twofold. First, we provide pre-qualification data that the Bluefors cryostat, including filtering and wiring, can support long-lived qubits. Second, we demonstrate that the Keysight system (controlled using Labber) provides a straightforward solution to perform these characterization measurements. This document is intended as a brief guide for starting an experimental platform for testing superconducting qubits. The setup described here is an immediate jumping off point for a suite of applications including testing quantum logical gates, quantum optics with microwaves, or even using the qubit itself as a sensitive probe of local electromagnetic fields. Qubit measurements rely on high performance of both the physical sample environment and the measurement electronics. An overview of the cryogenic system is shown in Figure 1, and an overview of the integration between the electronics and cryostat (including wiring details) is shown in Figure 2.","lang":"eng"}],"citation":{"mla":"Lake, Russell, et al. <i>The Bluefors Dilution Refrigerator as an Integrated Quantum Measurement System</i>. Bluefors Oy, 2021.","apa":"Lake, R., Simbierowicz, S., Krantz, P., Hassani, F., &#38; Fink, J. M. (2021). <i>The Bluefors dilution refrigerator as an integrated quantum measurement system</i>. Helsinki, Finland: Bluefors Oy.","short":"R. Lake, S. Simbierowicz, P. Krantz, F. Hassani, J.M. Fink, The Bluefors Dilution Refrigerator as an Integrated Quantum Measurement System, Bluefors Oy, Helsinki, Finland, 2021.","chicago":"Lake, Russell, Slawomir Simbierowicz, Philip Krantz, Farid Hassani, and Johannes M Fink. <i>The Bluefors Dilution Refrigerator as an Integrated Quantum Measurement System</i>. Helsinki, Finland: Bluefors Oy, 2021.","ieee":"R. Lake, S. Simbierowicz, P. Krantz, F. Hassani, and J. M. Fink, <i>The Bluefors dilution refrigerator as an integrated quantum measurement system</i>. Helsinki, Finland: Bluefors Oy, 2021.","ista":"Lake R, Simbierowicz S, Krantz P, Hassani F, Fink JM. 2021. The Bluefors dilution refrigerator as an integrated quantum measurement system, Helsinki, Finland: Bluefors Oy, 9p.","ama":"Lake R, Simbierowicz S, Krantz P, Hassani F, Fink JM. <i>The Bluefors Dilution Refrigerator as an Integrated Quantum Measurement System</i>. Helsinki, Finland: Bluefors Oy; 2021."},"place":"Helsinki, Finland","year":"2021","date_created":"2022-01-19T08:29:57Z","_id":"10644","day":"20","page":"9","main_file_link":[{"url":"https://bluefors.com/blog/integrated-quantum-measurement-system/","open_access":"1"}],"oa_version":"Published Version","article_processing_charge":"No","quality_controlled":"1","publication_status":"published","title":"The Bluefors dilution refrigerator as an integrated quantum measurement system"},{"month":"06","department":[{"_id":"JoFi"}],"status":"public","date_updated":"2022-01-19T09:11:39Z","language":[{"iso":"eng"}],"keyword":["Application note"],"alternative_title":["Bluefors Blog"],"date_published":"2021-06-03T00:00:00Z","type":"other_academic_publication","oa":1,"publisher":"Bluefors Oy","author":[{"last_name":"Simbierowicz","first_name":"Slawomir","full_name":"Simbierowicz, Slawomir"},{"first_name":"Chunyan","last_name":"Shi","full_name":"Shi, Chunyan"},{"full_name":"Collodo, Michele","first_name":"Michele","last_name":"Collodo"},{"full_name":"Kirste, Moritz","first_name":"Moritz","last_name":"Kirste"},{"id":"2AED110C-F248-11E8-B48F-1D18A9856A87","full_name":"Hassani, Farid","first_name":"Farid","last_name":"Hassani"},{"first_name":"Johannes M","last_name":"Fink","orcid":"0000-0001-8112-028X","id":"4B591CBA-F248-11E8-B48F-1D18A9856A87","full_name":"Fink, Johannes M"},{"last_name":"Bylander","first_name":"Jonas","full_name":"Bylander, Jonas"},{"first_name":"Daniel","last_name":"Perez Lozano","full_name":"Perez Lozano, Daniel"},{"last_name":"Lake","first_name":"Russell","full_name":"Lake, Russell"}],"user_id":"8b945eb4-e2f2-11eb-945a-df72226e66a9","_id":"10645","date_created":"2022-01-19T08:41:14Z","place":"Helsinki, Finland","year":"2021","citation":{"ama":"Simbierowicz S, Shi C, Collodo M, et al. <i>Qubit Energy-Relaxation Statistics in the Bluefors Quantum Measurement System</i>. Helsinki, Finland: Bluefors Oy; 2021.","ieee":"S. Simbierowicz <i>et al.</i>, <i>Qubit energy-relaxation statistics in the Bluefors quantum measurement system</i>. Helsinki, Finland: Bluefors Oy, 2021.","ista":"Simbierowicz S, Shi C, Collodo M, Kirste M, Hassani F, Fink JM, Bylander J, Perez Lozano D, Lake R. 2021. Qubit energy-relaxation statistics in the Bluefors quantum measurement system, Helsinki, Finland: Bluefors Oy, 8p.","chicago":"Simbierowicz, Slawomir, Chunyan Shi, Michele Collodo, Moritz Kirste, Farid Hassani, Johannes M Fink, Jonas Bylander, Daniel Perez Lozano, and Russell Lake. <i>Qubit Energy-Relaxation Statistics in the Bluefors Quantum Measurement System</i>. Helsinki, Finland: Bluefors Oy, 2021.","short":"S. Simbierowicz, C. Shi, M. Collodo, M. Kirste, F. Hassani, J.M. Fink, J. Bylander, D. Perez Lozano, R. Lake, Qubit Energy-Relaxation Statistics in the Bluefors Quantum Measurement System, Bluefors Oy, Helsinki, Finland, 2021.","apa":"Simbierowicz, S., Shi, C., Collodo, M., Kirste, M., Hassani, F., Fink, J. M., … Lake, R. (2021). <i>Qubit energy-relaxation statistics in the Bluefors quantum measurement system</i>. Helsinki, Finland: Bluefors Oy.","mla":"Simbierowicz, Slawomir, et al. <i>Qubit Energy-Relaxation Statistics in the Bluefors Quantum Measurement System</i>. Bluefors Oy, 2021."},"abstract":[{"text":"Superconducting qubits have emerged as a highly versatile and useful platform for quantum technological applications [1]. Bluefors and Zurich Instruments have supported the growth of this field from the 2010s onwards by providing well-engineered and reliable measurement infrastructure [2]– [6]. Having a long and stable qubit lifetime is a critical system property. Therefore, considerable effort has already gone into measuring qubit energy-relaxation timescales and their fluctuations, see Refs. [7]–[10] among others. Accurately extracting the statistics of a quantum device requires users to perform time consuming measurements. One measurement challenge is that the detection of the state-dependent\r\nresponse of a superconducting resonator due to a dispersively-coupled qubit requires an inherently low signal level. Consequently, measurements must be performed using a microwave probe that contains only a few microwave photons. Improving the signal-to-noise ratio (SNR) by using near-quantum limited parametric amplifiers as well as the use of optimized signal processing enabled by efficient room temperature instrumentation help to reduce measurement time. An empirical observation for fixed frequency transmons from recent literature is that as the energy-relaxation time 𝑇𝑇1 increases, so do its natural temporal fluctuations [7], [10]. This necessitates many repeated measurements to understand the statistics (see for example, Ref. [10]). In addition, as state-of-the-art qubits increase in lifetime, longer\r\nmeasurement times are expected to obtain accurate statistics. As described below, the scaling of the widths of the qubit energy-relaxation distributions also reveal clues about the origin of the energy-relaxation.","lang":"eng"}],"quality_controlled":"1","title":"Qubit energy-relaxation statistics in the Bluefors quantum measurement system","publication_status":"published","article_processing_charge":"No","oa_version":"Published Version","main_file_link":[{"url":"https://bluefors.com/blog/application-note-qubit-energy-relaxation-statistics-bluefors-quantum-measurement-system/","open_access":"1"}],"page":"8","day":"03"},{"title":"Optimizing AAV2/6 microglial targeting identified enhanced efficiency in the photoreceptor degenerative environment","publication_status":"published","file_date_updated":"2022-01-24T07:43:09Z","oa_version":"Published Version","article_processing_charge":"Yes","doi":"10.1016/j.omtm.2021.09.006","scopus_import":"1","article_type":"original","publication_identifier":{"eissn":["2329-0501"]},"acknowledgement":"This project has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement no. 715571). The research was supported by the Scientific Service Units (SSU) of IST Austria through resources provided by the Bioimaging Facility, the Life Science Facility, and the Pre-Clinical Facility, namely Sonja Haslinger and Michael Schunn for their animal colony management and support. We would also like to thank Chakrabarty Lab for sharing the plasmids for AAV2/6 production. Finally, we would like to thank the Siegert team members for discussion about the manuscript.","_id":"10655","date_created":"2022-01-23T23:01:28Z","file":[{"file_name":"2021_MolTherMethodsClinDev_Maes.pdf","success":1,"access_level":"open_access","relation":"main_file","file_size":4794147,"date_created":"2022-01-24T07:43:09Z","date_updated":"2022-01-24T07:43:09Z","content_type":"application/pdf","file_id":"10657","creator":"cchlebak","checksum":"77dc540e8011c5475031bdf6ccef20a6"}],"year":"2021","citation":{"ieee":"M. E. Maes, G. M. Wögenstein, G. Colombo, R. Casado Polanco, and S. Siegert, “Optimizing AAV2/6 microglial targeting identified enhanced efficiency in the photoreceptor degenerative environment,” <i>Molecular Therapy - Methods and Clinical Development</i>, vol. 23. Elsevier, pp. 210–224, 2021.","ista":"Maes ME, Wögenstein GM, Colombo G, Casado Polanco R, Siegert S. 2021. Optimizing AAV2/6 microglial targeting identified enhanced efficiency in the photoreceptor degenerative environment. Molecular Therapy - Methods and Clinical Development. 23, 210–224.","ama":"Maes ME, Wögenstein GM, Colombo G, Casado Polanco R, Siegert S. Optimizing AAV2/6 microglial targeting identified enhanced efficiency in the photoreceptor degenerative environment. <i>Molecular Therapy - Methods and Clinical Development</i>. 2021;23:210-224. doi:<a href=\"https://doi.org/10.1016/j.omtm.2021.09.006\">10.1016/j.omtm.2021.09.006</a>","mla":"Maes, Margaret E., et al. “Optimizing AAV2/6 Microglial Targeting Identified Enhanced Efficiency in the Photoreceptor Degenerative Environment.” <i>Molecular Therapy - Methods and Clinical Development</i>, vol. 23, Elsevier, 2021, pp. 210–24, doi:<a href=\"https://doi.org/10.1016/j.omtm.2021.09.006\">10.1016/j.omtm.2021.09.006</a>.","apa":"Maes, M. E., Wögenstein, G. M., Colombo, G., Casado Polanco, R., &#38; Siegert, S. (2021). Optimizing AAV2/6 microglial targeting identified enhanced efficiency in the photoreceptor degenerative environment. <i>Molecular Therapy - Methods and Clinical Development</i>. Elsevier. <a href=\"https://doi.org/10.1016/j.omtm.2021.09.006\">https://doi.org/10.1016/j.omtm.2021.09.006</a>","short":"M.E. Maes, G.M. Wögenstein, G. Colombo, R. Casado Polanco, S. Siegert, Molecular Therapy - Methods and Clinical Development 23 (2021) 210–224.","chicago":"Maes, Margaret E, Gabriele M. Wögenstein, Gloria Colombo, Raquel Casado Polanco, and Sandra Siegert. “Optimizing AAV2/6 Microglial Targeting Identified Enhanced Efficiency in the Photoreceptor Degenerative Environment.” <i>Molecular Therapy - Methods and Clinical Development</i>. Elsevier, 2021. <a href=\"https://doi.org/10.1016/j.omtm.2021.09.006\">https://doi.org/10.1016/j.omtm.2021.09.006</a>."},"abstract":[{"text":"Adeno-associated viruses (AAVs) are widely used to deliver genetic material in vivo to distinct cell types such as neurons or glial cells, allowing for targeted manipulation. Transduction of microglia is mostly excluded from this strategy, likely due to the cells’ heterogeneous state upon environmental changes, which makes AAV design challenging. Here, we established the retina as a model system for microglial AAV validation and optimization. First, we show that AAV2/6 transduced microglia in both synaptic layers, where layer preference corresponds to the intravitreal or subretinal delivery method. Surprisingly, we observed significantly enhanced microglial transduction during photoreceptor degeneration. Thus, we modified the AAV6 capsid to reduce heparin binding by introducing four point mutations (K531E, R576Q, K493S, and K459S), resulting in increased microglial transduction in the outer plexiform layer. Finally, to improve microglial-specific transduction, we validated a Cre-dependent transgene delivery cassette for use in combination with the Cx3cr1CreERT2 mouse line. Together, our results provide a foundation for future studies optimizing AAV-mediated microglia transduction and highlight that environmental conditions influence microglial transduction efficiency.\r\n","lang":"eng"}],"acknowledged_ssus":[{"_id":"Bio"},{"_id":"LifeSc"},{"_id":"PreCl"}],"oa":1,"volume":23,"author":[{"full_name":"Maes, Margaret E","id":"3838F452-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0001-9642-1085","last_name":"Maes","first_name":"Margaret E"},{"full_name":"Wögenstein, Gabriele M.","last_name":"Wögenstein","first_name":"Gabriele M."},{"first_name":"Gloria","last_name":"Colombo","orcid":"0000-0001-9434-8902","id":"3483CF6C-F248-11E8-B48F-1D18A9856A87","full_name":"Colombo, Gloria"},{"orcid":"0000-0001-8293-4568","id":"15240fc1-dbcd-11ea-9d1d-ac5a786425fd","full_name":"Casado Polanco, Raquel","first_name":"Raquel","last_name":"Casado Polanco"},{"full_name":"Siegert, Sandra","orcid":"0000-0001-8635-0877","id":"36ACD32E-F248-11E8-B48F-1D18A9856A87","last_name":"Siegert","first_name":"Sandra"}],"user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87","department":[{"_id":"SaSi"},{"_id":"SiHi"}],"publication":"Molecular Therapy - Methods and Clinical Development","ec_funded":1,"date_updated":"2023-11-16T13:12:03Z","intvolume":"        23","quality_controlled":"1","page":"210-224","day":"10","project":[{"name":"Microglia action towards neuronal circuit formation and function in health and disease","_id":"25D4A630-B435-11E9-9278-68D0E5697425","grant_number":"715571","call_identifier":"H2020"}],"tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","image":"/images/cc_by.png","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","short":"CC BY (4.0)"},"has_accepted_license":"1","external_id":{"isi":["000748748500019"]},"date_published":"2021-12-10T00:00:00Z","type":"journal_article","publisher":"Elsevier","month":"12","isi":1,"status":"public","language":[{"iso":"eng"}],"ddc":["570"]},{"external_id":{"arxiv":["2012.08185"]},"date_published":"2021-05-28T00:00:00Z","type":"conference","publisher":"AAAI Press","status":"public","month":"05","alternative_title":["Technical Tracks"],"language":[{"iso":"eng"}],"ddc":["000"],"quality_controlled":"1","day":"28","page":"3787-3795","has_accepted_license":"1","project":[{"name":"International IST Doctoral Program","_id":"2564DBCA-B435-11E9-9278-68D0E5697425","call_identifier":"H2020","grant_number":"665385"},{"name":"The Wittgenstein Prize","_id":"25F42A32-B435-11E9-9278-68D0E5697425","grant_number":"Z211","call_identifier":"FWF"},{"grant_number":"863818","call_identifier":"H2020","name":"Formal Methods for Stochastic Models: Algorithms and Applications","_id":"0599E47C-7A3F-11EA-A408-12923DDC885E"}],"issue":"5A","related_material":{"record":[{"id":"11362","status":"public","relation":"dissertation_contains"}]},"oa":1,"volume":35,"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","author":[{"first_name":"Thomas A","last_name":"Henzinger","orcid":"0000-0002-2985-7724","id":"40876CD8-F248-11E8-B48F-1D18A9856A87","full_name":"Henzinger, Thomas A"},{"id":"3DC22916-F248-11E8-B48F-1D18A9856A87","full_name":"Lechner, Mathias","first_name":"Mathias","last_name":"Lechner"},{"full_name":"Zikelic, Dorde","id":"294AA7A6-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-4681-1699","last_name":"Zikelic","first_name":"Dorde"}],"publication":"Proceedings of the AAAI Conference on Artificial Intelligence","ec_funded":1,"date_updated":"2025-07-14T09:10:11Z","department":[{"_id":"GradSch"},{"_id":"ToHe"}],"intvolume":"        35","arxiv":1,"file_date_updated":"2022-01-26T07:41:16Z","oa_version":"Published Version","article_processing_charge":"No","title":"Scalable verification of quantized neural networks","publication_status":"published","acknowledgement":"This research was supported in part by the Austrian Science Fund (FWF) under grant Z211-N23 (Wittgenstein\r\nAward), ERC CoG 863818 (FoRM-SMArt), and the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie Grant Agreement No. 665385.\r\n","publication_identifier":{"issn":["2159-5399"],"eissn":["2374-3468"],"isbn":["978-1-57735-866-4"]},"main_file_link":[{"url":"https://ojs.aaai.org/index.php/AAAI/article/view/16496","open_access":"1"}],"scopus_import":"1","_id":"10665","date_created":"2022-01-25T15:15:02Z","file":[{"file_size":137235,"date_updated":"2022-01-26T07:41:16Z","date_created":"2022-01-26T07:41:16Z","relation":"main_file","file_name":"16496-Article Text-19990-1-2-20210518 (1).pdf","success":1,"access_level":"open_access","checksum":"2bc8155b2526a70fba5b7301bc89dbd1","content_type":"application/pdf","creator":"mlechner","file_id":"10684"}],"conference":{"end_date":"2021-02-09","name":"AAAI: Association for the Advancement of Artificial Intelligence","location":"Virtual","start_date":"2021-02-02"},"abstract":[{"text":"Formal verification of neural networks is an active topic of research, and recent advances have significantly increased the size of the networks that verification tools can handle. However, most methods are designed for verification of an idealized model of the actual network which works over real arithmetic and ignores rounding imprecisions. This idealization is in stark contrast to network quantization, which is a technique that trades numerical precision for computational efficiency and is, therefore, often applied in practice. Neglecting rounding errors of such low-bit quantized neural networks has been shown to lead to wrong conclusions about the network’s correctness. Thus, the desired approach for verifying quantized neural networks would be one that takes these rounding errors\r\ninto account. In this paper, we show that verifying the bitexact implementation of quantized neural networks with bitvector specifications is PSPACE-hard, even though verifying idealized real-valued networks and satisfiability of bit-vector specifications alone are each in NP. Furthermore, we explore several practical heuristics toward closing the complexity gap between idealized and bit-exact verification. In particular, we propose three techniques for making SMT-based verification of quantized neural networks more scalable. Our experiments demonstrate that our proposed methods allow a speedup of up to three orders of magnitude over existing approaches.","lang":"eng"}],"year":"2021","citation":{"chicago":"Henzinger, Thomas A, Mathias Lechner, and Dorde Zikelic. “Scalable Verification of Quantized Neural Networks.” In <i>Proceedings of the AAAI Conference on Artificial Intelligence</i>, 35:3787–95. AAAI Press, 2021.","apa":"Henzinger, T. A., Lechner, M., &#38; Zikelic, D. (2021). Scalable verification of quantized neural networks. In <i>Proceedings of the AAAI Conference on Artificial Intelligence</i> (Vol. 35, pp. 3787–3795). Virtual: AAAI Press.","short":"T.A. Henzinger, M. Lechner, D. Zikelic, in:, Proceedings of the AAAI Conference on Artificial Intelligence, AAAI Press, 2021, pp. 3787–3795.","mla":"Henzinger, Thomas A., et al. “Scalable Verification of Quantized Neural Networks.” <i>Proceedings of the AAAI Conference on Artificial Intelligence</i>, vol. 35, no. 5A, AAAI Press, 2021, pp. 3787–95.","ama":"Henzinger TA, Lechner M, Zikelic D. Scalable verification of quantized neural networks. In: <i>Proceedings of the AAAI Conference on Artificial Intelligence</i>. Vol 35. AAAI Press; 2021:3787-3795.","ista":"Henzinger TA, Lechner M, Zikelic D. 2021. Scalable verification of quantized neural networks. Proceedings of the AAAI Conference on Artificial Intelligence. AAAI: Association for the Advancement of Artificial Intelligence, Technical Tracks, vol. 35, 3787–3795.","ieee":"T. A. Henzinger, M. Lechner, and D. Zikelic, “Scalable verification of quantized neural networks,” in <i>Proceedings of the AAAI Conference on Artificial Intelligence</i>, Virtual, 2021, vol. 35, no. 5A, pp. 3787–3795."}},{"page":"4140-4147","quality_controlled":"1","has_accepted_license":"1","license":"https://creativecommons.org/licenses/by-nc-nd/3.0/","tmp":{"name":"Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported (CC BY-NC-ND 3.0)","image":"/images/cc_by_nc_nd.png","short":"CC BY-NC-ND (3.0)","legal_code_url":"https://creativecommons.org/licenses/by-nc-nd/3.0/legalcode"},"project":[{"grant_number":"Z211","call_identifier":"FWF","name":"The Wittgenstein Prize","_id":"25F42A32-B435-11E9-9278-68D0E5697425"}],"date_published":"2021-01-01T00:00:00Z","external_id":{"isi":["000765738803040"],"arxiv":["2103.08187"]},"type":"conference","language":[{"iso":"eng"}],"ddc":["000"],"status":"public","isi":1,"acknowledgement":"M.L. and T.A.H. are supported in part by the Austrian Science Fund (FWF) under grant Z211-N23 (Wittgenstein Award). R.H. and D.R. are supported by Boeing and R.G. by Horizon-2020 ECSEL Project grant no. 783163 (iDev40).","publication_identifier":{"eissn":["2577-087X"],"isbn":["978-1-7281-9078-5"],"eisbn":["978-1-7281-9077-8"],"issn":["1050-4729"]},"doi":"10.1109/ICRA48506.2021.9561036","main_file_link":[{"url":"https://arxiv.org/abs/2103.08187","open_access":"1"}],"article_processing_charge":"No","oa_version":"None","title":"Adversarial training is not ready for robot learning","publication_status":"published","abstract":[{"text":"Adversarial training is an effective method to train deep learning models that are resilient to norm-bounded perturbations, with the cost of nominal performance drop. While adversarial training appears to enhance the robustness and safety of a deep model deployed in open-world decision-critical applications, counterintuitively, it induces undesired behaviors in robot learning settings. In this paper, we show theoretically and experimentally that neural controllers obtained via adversarial training are subjected to three types of defects, namely transient, systematic, and conditional errors. We first generalize adversarial training to a safety-domain optimization scheme allowing for more generic specifications. We then prove that such a learning process tends to cause certain error profiles. We support our theoretical results by a thorough experimental safety analysis in a robot-learning task. Our results suggest that adversarial training is not yet ready for robot learning.","lang":"eng"}],"year":"2021","citation":{"ama":"Lechner M, Hasani R, Grosu R, Rus D, Henzinger TA. Adversarial training is not ready for robot learning. In: <i>2021 IEEE International Conference on Robotics and Automation</i>. ICRA. ; 2021:4140-4147. doi:<a href=\"https://doi.org/10.1109/ICRA48506.2021.9561036\">10.1109/ICRA48506.2021.9561036</a>","ieee":"M. Lechner, R. Hasani, R. Grosu, D. Rus, and T. A. Henzinger, “Adversarial training is not ready for robot learning,” in <i>2021 IEEE International Conference on Robotics and Automation</i>, Xi’an, China, 2021, pp. 4140–4147.","ista":"Lechner M, Hasani R, Grosu R, Rus D, Henzinger TA. 2021. Adversarial training is not ready for robot learning. 2021 IEEE International Conference on Robotics and Automation. ICRA: International Conference on Robotics and AutomationICRA, 4140–4147.","mla":"Lechner, Mathias, et al. “Adversarial Training Is Not Ready for Robot Learning.” <i>2021 IEEE International Conference on Robotics and Automation</i>, 2021, pp. 4140–47, doi:<a href=\"https://doi.org/10.1109/ICRA48506.2021.9561036\">10.1109/ICRA48506.2021.9561036</a>.","short":"M. Lechner, R. Hasani, R. Grosu, D. Rus, T.A. Henzinger, in:, 2021 IEEE International Conference on Robotics and Automation, 2021, pp. 4140–4147.","apa":"Lechner, M., Hasani, R., Grosu, R., Rus, D., &#38; Henzinger, T. A. (2021). Adversarial training is not ready for robot learning. In <i>2021 IEEE International Conference on Robotics and Automation</i> (pp. 4140–4147). Xi’an, China. <a href=\"https://doi.org/10.1109/ICRA48506.2021.9561036\">https://doi.org/10.1109/ICRA48506.2021.9561036</a>","chicago":"Lechner, Mathias, Ramin Hasani, Radu Grosu, Daniela Rus, and Thomas A Henzinger. “Adversarial Training Is Not Ready for Robot Learning.” In <i>2021 IEEE International Conference on Robotics and Automation</i>, 4140–47. ICRA, 2021. <a href=\"https://doi.org/10.1109/ICRA48506.2021.9561036\">https://doi.org/10.1109/ICRA48506.2021.9561036</a>."},"_id":"10666","date_created":"2022-01-25T15:44:54Z","conference":{"start_date":"2021-05-30","end_date":"2021-06-05","name":"ICRA: International Conference on Robotics and Automation","location":"Xi'an, China"},"user_id":"4359f0d1-fa6c-11eb-b949-802e58b17ae8","author":[{"last_name":"Lechner","first_name":"Mathias","full_name":"Lechner, Mathias","id":"3DC22916-F248-11E8-B48F-1D18A9856A87"},{"first_name":"Ramin","last_name":"Hasani","full_name":"Hasani, Ramin"},{"full_name":"Grosu, Radu","last_name":"Grosu","first_name":"Radu"},{"last_name":"Rus","first_name":"Daniela","full_name":"Rus, Daniela"},{"first_name":"Thomas A","last_name":"Henzinger","orcid":"0000-0002-2985-7724","id":"40876CD8-F248-11E8-B48F-1D18A9856A87","full_name":"Henzinger, Thomas A"}],"oa":1,"related_material":{"record":[{"id":"11362","status":"public","relation":"dissertation_contains"}]},"series_title":"ICRA","arxiv":1,"publication":"2021 IEEE International Conference on Robotics and Automation","date_updated":"2023-08-17T06:58:38Z","department":[{"_id":"GradSch"},{"_id":"ToHe"}]},{"language":[{"iso":"eng"}],"ddc":["000"],"alternative_title":[" Advances in Neural Information Processing Systems"],"month":"12","status":"public","date_published":"2021-12-01T00:00:00Z","external_id":{"arxiv":["2111.03165"]},"type":"conference","has_accepted_license":"1","tmp":{"name":"Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported (CC BY-NC-ND 3.0)","image":"/images/cc_by_nc_nd.png","short":"CC BY-NC-ND (3.0)","legal_code_url":"https://creativecommons.org/licenses/by-nc-nd/3.0/legalcode"},"project":[{"name":"International IST Doctoral Program","_id":"2564DBCA-B435-11E9-9278-68D0E5697425","call_identifier":"H2020","grant_number":"665385"},{"grant_number":"863818","call_identifier":"H2020","name":"Formal Methods for Stochastic Models: Algorithms and Applications","_id":"0599E47C-7A3F-11EA-A408-12923DDC885E"},{"name":"The Wittgenstein Prize","_id":"25F42A32-B435-11E9-9278-68D0E5697425","call_identifier":"FWF","grant_number":"Z211"}],"day":"01","quality_controlled":"1","arxiv":1,"department":[{"_id":"GradSch"},{"_id":"ToHe"},{"_id":"KrCh"}],"publication":"35th Conference on Neural Information Processing Systems","ec_funded":1,"date_updated":"2025-07-14T09:10:12Z","author":[{"first_name":"Mathias","last_name":"Lechner","id":"3DC22916-F248-11E8-B48F-1D18A9856A87","full_name":"Lechner, Mathias"},{"full_name":"Žikelić, Ðorđe","last_name":"Žikelić","first_name":"Ðorđe"},{"first_name":"Krishnendu","last_name":"Chatterjee","orcid":"0000-0002-4561-241X","id":"2E5DCA20-F248-11E8-B48F-1D18A9856A87","full_name":"Chatterjee, Krishnendu"},{"first_name":"Thomas A","last_name":"Henzinger","orcid":"0000-0002-2985-7724","id":"40876CD8-F248-11E8-B48F-1D18A9856A87","full_name":"Henzinger, Thomas A"}],"user_id":"2EBD1598-F248-11E8-B48F-1D18A9856A87","related_material":{"record":[{"relation":"dissertation_contains","status":"public","id":"11362"}]},"oa":1,"year":"2021","citation":{"chicago":"Lechner, Mathias, Ðorđe Žikelić, Krishnendu Chatterjee, and Thomas A Henzinger. “Infinite Time Horizon Safety of Bayesian Neural Networks.” In <i>35th Conference on Neural Information Processing Systems</i>, 2021. <a href=\"https://doi.org/10.48550/arXiv.2111.03165\">https://doi.org/10.48550/arXiv.2111.03165</a>.","apa":"Lechner, M., Žikelić, Ð., Chatterjee, K., &#38; Henzinger, T. A. (2021). Infinite time horizon safety of Bayesian neural networks. In <i>35th Conference on Neural Information Processing Systems</i>. Virtual. <a href=\"https://doi.org/10.48550/arXiv.2111.03165\">https://doi.org/10.48550/arXiv.2111.03165</a>","short":"M. Lechner, Ð. Žikelić, K. Chatterjee, T.A. Henzinger, in:, 35th Conference on Neural Information Processing Systems, 2021.","mla":"Lechner, Mathias, et al. “Infinite Time Horizon Safety of Bayesian Neural Networks.” <i>35th Conference on Neural Information Processing Systems</i>, 2021, doi:<a href=\"https://doi.org/10.48550/arXiv.2111.03165\">10.48550/arXiv.2111.03165</a>.","ama":"Lechner M, Žikelić Ð, Chatterjee K, Henzinger TA. Infinite time horizon safety of Bayesian neural networks. In: <i>35th Conference on Neural Information Processing Systems</i>. ; 2021. doi:<a href=\"https://doi.org/10.48550/arXiv.2111.03165\">10.48550/arXiv.2111.03165</a>","ista":"Lechner M, Žikelić Ð, Chatterjee K, Henzinger TA. 2021. Infinite time horizon safety of Bayesian neural networks. 35th Conference on Neural Information Processing Systems. NeurIPS: Neural Information Processing Systems,  Advances in Neural Information Processing Systems, .","ieee":"M. Lechner, Ð. Žikelić, K. Chatterjee, and T. A. Henzinger, “Infinite time horizon safety of Bayesian neural networks,” in <i>35th Conference on Neural Information Processing Systems</i>, Virtual, 2021."},"abstract":[{"text":"Bayesian neural networks (BNNs) place distributions over the weights of a neural network to model uncertainty in the data and the network's prediction. We consider the problem of verifying safety when running a Bayesian neural network policy in a feedback loop with infinite time horizon systems. Compared to the existing sampling-based approaches, which are inapplicable to the infinite time horizon setting, we train a separate deterministic neural network that serves as an infinite time horizon safety certificate. In particular, we show that the certificate network guarantees the safety of the system over a subset of the BNN weight posterior's support. Our method first computes a safe weight set and then alters the BNN's weight posterior to reject samples outside this set. Moreover, we show how to extend our approach to a safe-exploration reinforcement learning setting, in order to avoid unsafe trajectories during the training of the policy. We evaluate our approach on a series of reinforcement learning benchmarks, including non-Lyapunovian safety specifications.","lang":"eng"}],"conference":{"start_date":"2021-12-06","end_date":"2021-12-10","location":"Virtual","name":"NeurIPS: Neural Information Processing Systems"},"_id":"10667","file":[{"date_created":"2022-01-26T07:39:59Z","file_size":452492,"date_updated":"2022-01-26T07:39:59Z","relation":"main_file","access_level":"open_access","success":1,"file_name":"infinite_time_horizon_safety_o.pdf","checksum":"0fc0f852525c10dda9cc9ffea07fb4e4","file_id":"10682","creator":"mlechner","content_type":"application/pdf"}],"date_created":"2022-01-25T15:45:58Z","doi":"10.48550/arXiv.2111.03165","main_file_link":[{"url":"https://proceedings.neurips.cc/paper/2021/hash/544defa9fddff50c53b71c43e0da72be-Abstract.html","open_access":"1"}],"acknowledgement":"This research was supported in part by the Austrian Science Fund (FWF) under grant Z211-N23 (Wittgenstein Award), ERC CoG 863818 (FoRM-SMArt), and the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie Grant Agreement No. 665385.","title":"Infinite time horizon safety of Bayesian neural networks","publication_status":"published","file_date_updated":"2022-01-26T07:39:59Z","oa_version":"Published Version","article_processing_charge":"No"},{"publisher":"ML Research Press","date_published":"2021-07-01T00:00:00Z","type":"conference","language":[{"iso":"eng"}],"ddc":["000"],"alternative_title":["PMLR"],"month":"07","status":"public","page":"478-489","day":"01","quality_controlled":"1","tmp":{"name":"Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported (CC BY-NC-ND 3.0)","image":"/images/cc_by_nc_nd.png","short":"CC BY-NC-ND (3.0)","legal_code_url":"https://creativecommons.org/licenses/by-nc-nd/3.0/legalcode"},"project":[{"grant_number":"Z211","call_identifier":"FWF","name":"The Wittgenstein Prize","_id":"25F42A32-B435-11E9-9278-68D0E5697425"}],"has_accepted_license":"1","author":[{"last_name":"Babaiee","first_name":"Zahra","full_name":"Babaiee, Zahra"},{"full_name":"Hasani, Ramin","last_name":"Hasani","first_name":"Ramin"},{"full_name":"Lechner, Mathias","id":"3DC22916-F248-11E8-B48F-1D18A9856A87","last_name":"Lechner","first_name":"Mathias"},{"last_name":"Rus","first_name":"Daniela","full_name":"Rus, Daniela"},{"full_name":"Grosu, Radu","first_name":"Radu","last_name":"Grosu"}],"user_id":"2EBD1598-F248-11E8-B48F-1D18A9856A87","oa":1,"volume":139,"intvolume":"       139","department":[{"_id":"GradSch"},{"_id":"ToHe"}],"publication":"Proceedings of the 38th International Conference on Machine Learning","date_updated":"2022-05-04T15:02:27Z","main_file_link":[{"open_access":"1","url":"https://proceedings.mlr.press/v139/babaiee21a"}],"acknowledgement":"Z.B. is supported by the Doctoral College Resilient Embedded Systems, which is run jointly by the TU Wien’s Faculty of Informatics and the UAS Technikum Wien. R.G. is partially supported by the Horizon 2020 Era-Permed project Persorad, and ECSEL Project grant no. 783163 (iDev40). R.H and D.R were partially supported by Boeing and MIT. M.L. is supported in part by the Austrian Science Fund (FWF) under grant Z211-N23 (Wittgenstein Award).","publication_identifier":{"issn":["2640-3498"]},"publication_status":"published","title":"On-off center-surround receptive fields for accurate and robust image classification","file_date_updated":"2022-01-26T07:38:32Z","article_processing_charge":"No","oa_version":"Published Version","year":"2021","citation":{"mla":"Babaiee, Zahra, et al. “On-off Center-Surround Receptive Fields for Accurate and Robust Image Classification.” <i>Proceedings of the 38th International Conference on Machine Learning</i>, vol. 139, ML Research Press, 2021, pp. 478–89.","chicago":"Babaiee, Zahra, Ramin Hasani, Mathias Lechner, Daniela Rus, and Radu Grosu. “On-off Center-Surround Receptive Fields for Accurate and Robust Image Classification.” In <i>Proceedings of the 38th International Conference on Machine Learning</i>, 139:478–89. ML Research Press, 2021.","apa":"Babaiee, Z., Hasani, R., Lechner, M., Rus, D., &#38; Grosu, R. (2021). On-off center-surround receptive fields for accurate and robust image classification. In <i>Proceedings of the 38th International Conference on Machine Learning</i> (Vol. 139, pp. 478–489). Virtual: ML Research Press.","short":"Z. Babaiee, R. Hasani, M. Lechner, D. Rus, R. Grosu, in:, Proceedings of the 38th International Conference on Machine Learning, ML Research Press, 2021, pp. 478–489.","ieee":"Z. Babaiee, R. Hasani, M. Lechner, D. Rus, and R. Grosu, “On-off center-surround receptive fields for accurate and robust image classification,” in <i>Proceedings of the 38th International Conference on Machine Learning</i>, Virtual, 2021, vol. 139, pp. 478–489.","ista":"Babaiee Z, Hasani R, Lechner M, Rus D, Grosu R. 2021. On-off center-surround receptive fields for accurate and robust image classification. Proceedings of the 38th International Conference on Machine Learning. ML: Machine Learning, PMLR, vol. 139, 478–489.","ama":"Babaiee Z, Hasani R, Lechner M, Rus D, Grosu R. On-off center-surround receptive fields for accurate and robust image classification. In: <i>Proceedings of the 38th International Conference on Machine Learning</i>. Vol 139. ML Research Press; 2021:478-489."},"abstract":[{"lang":"eng","text":"Robustness to variations in lighting conditions is a key objective for any deep vision system. To this end, our paper extends the receptive field of convolutional neural networks with two residual components, ubiquitous in the visual processing system of vertebrates: On-center and off-center pathways, with an excitatory center and inhibitory surround; OOCS for short. The On-center pathway is excited by the presence of a light stimulus in its center, but not in its surround, whereas the Off-center pathway is excited by the absence of a light stimulus in its center, but not in its surround. We design OOCS pathways via a difference of Gaussians, with their variance computed analytically from the size of the receptive fields. OOCS pathways complement each other in their response to light stimuli, ensuring this way a strong edge-detection capability, and as a result an accurate and robust inference under challenging lighting conditions. We provide extensive empirical evidence showing that networks supplied with OOCS pathways gain accuracy and illumination-robustness from the novel edge representation, compared to other baselines."}],"conference":{"end_date":"2021-07-24","name":"ML: Machine Learning","location":"Virtual","start_date":"2021-07-18"},"_id":"10668","file":[{"file_size":4246561,"relation":"main_file","date_updated":"2022-01-26T07:38:32Z","date_created":"2022-01-26T07:38:32Z","file_name":"babaiee21a.pdf","success":1,"access_level":"open_access","checksum":"d30eae62561bb517d9f978437d7677db","creator":"mlechner","file_id":"10681","content_type":"application/pdf"}],"date_created":"2022-01-25T15:46:33Z"},{"day":"28","page":"11525-11535","quality_controlled":"1","project":[{"call_identifier":"FWF","grant_number":"Z211","name":"The Wittgenstein Prize","_id":"25F42A32-B435-11E9-9278-68D0E5697425"}],"has_accepted_license":"1","issue":"13","publisher":"AAAI Press","type":"conference","external_id":{"arxiv":["2012.08863"]},"date_published":"2021-05-28T00:00:00Z","alternative_title":["Technical Tracks"],"ddc":["000"],"language":[{"iso":"eng"}],"status":"public","month":"05","publication_identifier":{"isbn":["978-1-57735-866-4"],"eissn":["2374-3468"],"issn":["2159-5399"]},"acknowledgement":"The authors would like to thank the reviewers for their insightful comments. RH and RG were partially supported by\r\nHorizon-2020 ECSEL Project grant No. 783163 (iDev40). RH was partially supported by Boeing. ML was supported\r\nin part by the Austrian Science Fund (FWF) under grant Z211-N23 (Wittgenstein Award). SG was funded by FWF\r\nproject W1255-N23. JC was partially supported by NAWA Polish Returns grant PPN/PPO/2018/1/00029. SS was supported by NSF awards DCL-2040599, CCF-1918225, and CPS-1446832.\r\n","main_file_link":[{"open_access":"1","url":"https://ojs.aaai.org/index.php/AAAI/article/view/17372"}],"oa_version":"Published Version","article_processing_charge":"No","file_date_updated":"2022-01-26T07:38:08Z","publication_status":"published","title":"On the verification of neural ODEs with stochastic guarantees","abstract":[{"lang":"eng","text":"We show that Neural ODEs, an emerging class of timecontinuous neural networks, can be verified by solving a set of global-optimization problems. For this purpose, we introduce Stochastic Lagrangian Reachability (SLR), an\r\nabstraction-based technique for constructing a tight Reachtube (an over-approximation of the set of reachable states\r\nover a given time-horizon), and provide stochastic guarantees in the form of confidence intervals for the Reachtube bounds. SLR inherently avoids the infamous wrapping effect (accumulation of over-approximation errors) by performing local optimization steps to expand safe regions instead of repeatedly forward-propagating them as is done by deterministic reachability methods. To enable fast local optimizations, we introduce a novel forward-mode adjoint sensitivity method to compute gradients without the need for backpropagation. Finally, we establish asymptotic and non-asymptotic convergence rates for SLR."}],"citation":{"mla":"Grunbacher, Sophie, et al. “On the Verification of Neural ODEs with Stochastic Guarantees.” <i>Proceedings of the AAAI Conference on Artificial Intelligence</i>, vol. 35, no. 13, AAAI Press, 2021, pp. 11525–35.","short":"S. Grunbacher, R. Hasani, M. Lechner, J. Cyranka, S.A. Smolka, R. Grosu, in:, Proceedings of the AAAI Conference on Artificial Intelligence, AAAI Press, 2021, pp. 11525–11535.","apa":"Grunbacher, S., Hasani, R., Lechner, M., Cyranka, J., Smolka, S. A., &#38; Grosu, R. (2021). On the verification of neural ODEs with stochastic guarantees. In <i>Proceedings of the AAAI Conference on Artificial Intelligence</i> (Vol. 35, pp. 11525–11535). Virtual: AAAI Press.","chicago":"Grunbacher, Sophie, Ramin Hasani, Mathias Lechner, Jacek Cyranka, Scott A Smolka, and Radu Grosu. “On the Verification of Neural ODEs with Stochastic Guarantees.” In <i>Proceedings of the AAAI Conference on Artificial Intelligence</i>, 35:11525–35. AAAI Press, 2021.","ama":"Grunbacher S, Hasani R, Lechner M, Cyranka J, Smolka SA, Grosu R. On the verification of neural ODEs with stochastic guarantees. In: <i>Proceedings of the AAAI Conference on Artificial Intelligence</i>. Vol 35. AAAI Press; 2021:11525-11535.","ista":"Grunbacher S, Hasani R, Lechner M, Cyranka J, Smolka SA, Grosu R. 2021. On the verification of neural ODEs with stochastic guarantees. Proceedings of the AAAI Conference on Artificial Intelligence. AAAI: Association for the Advancement of Artificial Intelligence, Technical Tracks, vol. 35, 11525–11535.","ieee":"S. Grunbacher, R. Hasani, M. Lechner, J. Cyranka, S. A. Smolka, and R. Grosu, “On the verification of neural ODEs with stochastic guarantees,” in <i>Proceedings of the AAAI Conference on Artificial Intelligence</i>, Virtual, 2021, vol. 35, no. 13, pp. 11525–11535."},"year":"2021","file":[{"checksum":"468d07041e282a1d46ffdae92f709630","content_type":"application/pdf","file_id":"10680","creator":"mlechner","file_size":286906,"relation":"main_file","date_created":"2022-01-26T07:38:08Z","date_updated":"2022-01-26T07:38:08Z","success":1,"access_level":"open_access","file_name":"17372-Article Text-20866-1-2-20210518.pdf"}],"date_created":"2022-01-25T15:47:20Z","_id":"10669","conference":{"end_date":"2021-02-09","location":"Virtual","name":"AAAI: Association for the Advancement of Artificial Intelligence","start_date":"2021-02-02"},"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","author":[{"full_name":"Grunbacher, Sophie","first_name":"Sophie","last_name":"Grunbacher"},{"last_name":"Hasani","first_name":"Ramin","full_name":"Hasani, Ramin"},{"full_name":"Lechner, Mathias","id":"3DC22916-F248-11E8-B48F-1D18A9856A87","last_name":"Lechner","first_name":"Mathias"},{"first_name":"Jacek","last_name":"Cyranka","full_name":"Cyranka, Jacek"},{"full_name":"Smolka, Scott A","last_name":"Smolka","first_name":"Scott A"},{"first_name":"Radu","last_name":"Grosu","full_name":"Grosu, Radu"}],"volume":35,"oa":1,"intvolume":"        35","arxiv":1,"date_updated":"2022-05-24T06:33:14Z","publication":"Proceedings of the AAAI Conference on Artificial Intelligence","department":[{"_id":"GradSch"},{"_id":"ToHe"}]},{"oa":1,"user_id":"8b945eb4-e2f2-11eb-945a-df72226e66a9","author":[{"first_name":"Charles J","last_name":"Vorbach","full_name":"Vorbach, Charles J"},{"full_name":"Hasani, Ramin","last_name":"Hasani","first_name":"Ramin"},{"last_name":"Amini","first_name":"Alexander","full_name":"Amini, Alexander"},{"first_name":"Mathias","last_name":"Lechner","id":"3DC22916-F248-11E8-B48F-1D18A9856A87","full_name":"Lechner, Mathias"},{"last_name":"Rus","first_name":"Daniela","full_name":"Rus, Daniela"}],"publication":"35th Conference on Neural Information Processing Systems","date_updated":"2022-01-26T14:33:31Z","department":[{"_id":"GradSch"},{"_id":"ToHe"}],"arxiv":1,"file_date_updated":"2022-01-26T07:37:24Z","oa_version":"Published Version","article_processing_charge":"No","title":"Causal navigation by continuous-time neural networks","publication_status":"published","acknowledgement":"C.V., R.H. A.A. and D.R. are partially supported by Boeing and MIT. A.A. is supported by the National Science Foundation (NSF) Graduate Research Fellowship Program. M.L. is supported in part by the Austrian Science Fund (FWF) under grant Z211-N23 (Wittgenstein Award). Research was sponsored by the United States Air Force Research Laboratory and the United States Air Force Artificial Intelligence Accelerator and was accomplished under Cooperative Agreement Number FA8750-19-2-1000. The views and conclusions contained in this document are those of the authors\r\nand should not be interpreted as representing the official policies, either expressed or implied, of the United States Air Force or the U.S. Government. The U.S. Government is authorized to reproduce and distribute reprints for Government purposes notwithstanding any copyright notation herein.\r\n","main_file_link":[{"open_access":"1","url":"https://proceedings.neurips.cc/paper/2021/hash/67ba02d73c54f0b83c05507b7fb7267f-Abstract.html"}],"_id":"10670","date_created":"2022-01-25T15:47:50Z","file":[{"date_created":"2022-01-26T07:37:24Z","file_size":6841228,"date_updated":"2022-01-26T07:37:24Z","relation":"main_file","success":1,"access_level":"open_access","file_name":"NeurIPS-2021-causal-navigation-by-continuous-time-neural-networks-Paper.pdf","checksum":"be81f0ade174a8c9b2d4fe09590b2021","file_id":"10679","creator":"mlechner","content_type":"application/pdf"}],"conference":{"location":"Virtual","name":"NeurIPS: Neural Information Processing Systems","end_date":"2021-12-10","start_date":"2021-12-06"},"abstract":[{"text":"Imitation learning enables high-fidelity, vision-based learning of policies within rich, photorealistic environments. However, such techniques often rely on traditional discrete-time neural models and face difficulties in generalizing to domain shifts by failing to account for the causal relationships between the agent and the environment. In this paper, we propose a theoretical and experimental framework for learning causal representations using continuous-time neural networks, specifically over their discrete-time counterparts. We evaluate our method in the context of visual-control learning of drones over a series of complex tasks, ranging from short- and long-term navigation, to chasing static and dynamic objects through photorealistic environments. Our results demonstrate that causal continuous-time\r\ndeep models can perform robust navigation tasks, where advanced recurrent models fail. These models learn complex causal control representations directly from raw visual inputs and scale to solve a variety of tasks using imitation learning.","lang":"eng"}],"year":"2021","citation":{"ista":"Vorbach CJ, Hasani R, Amini A, Lechner M, Rus D. 2021. Causal navigation by continuous-time neural networks. 35th Conference on Neural Information Processing Systems. NeurIPS: Neural Information Processing Systems,  Advances in Neural Information Processing Systems, .","ieee":"C. J. Vorbach, R. Hasani, A. Amini, M. Lechner, and D. Rus, “Causal navigation by continuous-time neural networks,” in <i>35th Conference on Neural Information Processing Systems</i>, Virtual, 2021.","ama":"Vorbach CJ, Hasani R, Amini A, Lechner M, Rus D. Causal navigation by continuous-time neural networks. In: <i>35th Conference on Neural Information Processing Systems</i>. ; 2021.","mla":"Vorbach, Charles J., et al. “Causal Navigation by Continuous-Time Neural Networks.” <i>35th Conference on Neural Information Processing Systems</i>, 2021.","short":"C.J. Vorbach, R. Hasani, A. Amini, M. Lechner, D. Rus, in:, 35th Conference on Neural Information Processing Systems, 2021.","apa":"Vorbach, C. J., Hasani, R., Amini, A., Lechner, M., &#38; Rus, D. (2021). Causal navigation by continuous-time neural networks. In <i>35th Conference on Neural Information Processing Systems</i>. Virtual.","chicago":"Vorbach, Charles J, Ramin Hasani, Alexander Amini, Mathias Lechner, and Daniela Rus. “Causal Navigation by Continuous-Time Neural Networks.” In <i>35th Conference on Neural Information Processing Systems</i>, 2021."},"date_published":"2021-12-01T00:00:00Z","external_id":{"arxiv":["2106.08314"]},"type":"conference","status":"public","month":"12","alternative_title":[" Advances in Neural Information Processing Systems"],"language":[{"iso":"eng"}],"ddc":["000"],"quality_controlled":"1","day":"01","has_accepted_license":"1","tmp":{"name":"Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported (CC BY-NC-ND 3.0)","image":"/images/cc_by_nc_nd.png","short":"CC BY-NC-ND (3.0)","legal_code_url":"https://creativecommons.org/licenses/by-nc-nd/3.0/legalcode"},"project":[{"call_identifier":"FWF","grant_number":"Z211","name":"The Wittgenstein Prize","_id":"25F42A32-B435-11E9-9278-68D0E5697425"}]},{"conference":{"start_date":"2021-02-02","name":"AAAI: Association for the Advancement of Artificial Intelligence","location":"Virtual","end_date":"2021-02-09"},"_id":"10671","file":[{"date_created":"2022-01-26T07:36:03Z","relation":"main_file","date_updated":"2022-01-26T07:36:03Z","file_size":4302669,"access_level":"open_access","success":1,"file_name":"16936-Article Text-20430-1-2-20210518 (1).pdf","checksum":"0f06995fba06dbcfa7ed965fc66027ff","content_type":"application/pdf","creator":"mlechner","file_id":"10678"}],"date_created":"2022-01-25T15:48:36Z","year":"2021","citation":{"ama":"Hasani R, Lechner M, Amini A, Rus D, Grosu R. Liquid time-constant networks. In: <i>Proceedings of the AAAI Conference on Artificial Intelligence</i>. Vol 35. AAAI Press; 2021:7657-7666.","ista":"Hasani R, Lechner M, Amini A, Rus D, Grosu R. 2021. Liquid time-constant networks. Proceedings of the AAAI Conference on Artificial Intelligence. AAAI: Association for the Advancement of Artificial Intelligence, Technical Tracks, vol. 35, 7657–7666.","ieee":"R. Hasani, M. Lechner, A. Amini, D. Rus, and R. Grosu, “Liquid time-constant networks,” in <i>Proceedings of the AAAI Conference on Artificial Intelligence</i>, Virtual, 2021, vol. 35, no. 9, pp. 7657–7666.","chicago":"Hasani, Ramin, Mathias Lechner, Alexander Amini, Daniela Rus, and Radu Grosu. “Liquid Time-Constant Networks.” In <i>Proceedings of the AAAI Conference on Artificial Intelligence</i>, 35:7657–66. AAAI Press, 2021.","short":"R. Hasani, M. Lechner, A. Amini, D. Rus, R. Grosu, in:, Proceedings of the AAAI Conference on Artificial Intelligence, AAAI Press, 2021, pp. 7657–7666.","apa":"Hasani, R., Lechner, M., Amini, A., Rus, D., &#38; Grosu, R. (2021). Liquid time-constant networks. In <i>Proceedings of the AAAI Conference on Artificial Intelligence</i> (Vol. 35, pp. 7657–7666). Virtual: AAAI Press.","mla":"Hasani, Ramin, et al. “Liquid Time-Constant Networks.” <i>Proceedings of the AAAI Conference on Artificial Intelligence</i>, vol. 35, no. 9, AAAI Press, 2021, pp. 7657–66."},"abstract":[{"lang":"eng","text":"We introduce a new class of time-continuous recurrent neural network models. Instead of declaring a learning system’s dynamics by implicit nonlinearities, we construct networks of linear first-order dynamical systems modulated via nonlinear interlinked gates. The resulting models represent dynamical systems with varying (i.e., liquid) time-constants coupled to their hidden state, with outputs being computed by numerical differential equation solvers. These neural networks exhibit stable and bounded behavior, yield superior expressivity within the family of neural ordinary differential equations, and give rise to improved performance on time-series prediction tasks. To demonstrate these properties, we first take a theoretical approach to find bounds over their dynamics, and compute their expressive power by the trajectory length measure in a latent trajectory space. We then conduct a series of time-series prediction experiments to manifest the approximation capability of Liquid Time-Constant Networks (LTCs) compared to classical and modern RNNs."}],"title":"Liquid time-constant networks","publication_status":"published","file_date_updated":"2022-01-26T07:36:03Z","article_processing_charge":"No","oa_version":"Published Version","main_file_link":[{"url":"https://ojs.aaai.org/index.php/AAAI/article/view/16936","open_access":"1"}],"acknowledgement":"R.H. and D.R. are partially supported by Boeing. R.H. and R.G. were partially supported by the Horizon-2020 ECSEL\r\nProject grant No. 783163 (iDev40). M.L. was supported in part by the Austrian Science Fund (FWF) under grant Z211-N23 (Wittgenstein Award). A.A. is supported by the National Science Foundation (NSF) Graduate Research Fellowship Program. This research work is partially drawn from the PhD dissertation of R.H.","publication_identifier":{"eissn":["2374-3468"],"isbn":["978-1-57735-866-4"],"issn":["2159-5399"]},"department":[{"_id":"GradSch"},{"_id":"ToHe"}],"publication":"Proceedings of the AAAI Conference on Artificial Intelligence","date_updated":"2022-05-24T06:36:54Z","arxiv":1,"intvolume":"        35","oa":1,"volume":35,"author":[{"full_name":"Hasani, Ramin","last_name":"Hasani","first_name":"Ramin"},{"id":"3DC22916-F248-11E8-B48F-1D18A9856A87","full_name":"Lechner, Mathias","first_name":"Mathias","last_name":"Lechner"},{"first_name":"Alexander","last_name":"Amini","full_name":"Amini, Alexander"},{"last_name":"Rus","first_name":"Daniela","full_name":"Rus, Daniela"},{"full_name":"Grosu, Radu","first_name":"Radu","last_name":"Grosu"}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","issue":"9","project":[{"_id":"25F42A32-B435-11E9-9278-68D0E5697425","name":"The Wittgenstein Prize","call_identifier":"FWF","grant_number":"Z211"}],"has_accepted_license":"1","quality_controlled":"1","page":"7657-7666","day":"28","month":"05","status":"public","language":[{"iso":"eng"}],"ddc":["000"],"alternative_title":["Technical Tracks"],"date_published":"2021-05-28T00:00:00Z","external_id":{"arxiv":["2006.04439"]},"type":"conference","publisher":"AAAI Press"}]