[{"keyword":["Application note"],"year":"2021","article_processing_charge":"No","author":[{"last_name":"Lake","full_name":"Lake, Russell","first_name":"Russell"},{"full_name":"Simbierowicz, Slawomir","last_name":"Simbierowicz","first_name":"Slawomir"},{"last_name":"Krantz","full_name":"Krantz, Philip","first_name":"Philip"},{"full_name":"Hassani, Farid","last_name":"Hassani","id":"2AED110C-F248-11E8-B48F-1D18A9856A87","first_name":"Farid"},{"orcid":"0000-0001-8112-028X","full_name":"Fink, Johannes M","last_name":"Fink","id":"4B591CBA-F248-11E8-B48F-1D18A9856A87","first_name":"Johannes M"}],"date_published":"2021-04-20T00:00:00Z","month":"04","department":[{"_id":"JoFi"}],"title":"The Bluefors dilution refrigerator as an integrated quantum measurement system","date_updated":"2022-01-19T09:11:33Z","day":"20","date_created":"2022-01-19T08:29:57Z","_id":"10644","publisher":"Bluefors Oy","page":"9","oa_version":"Published Version","oa":1,"user_id":"8b945eb4-e2f2-11eb-945a-df72226e66a9","quality_controlled":"1","place":"Helsinki, Finland","status":"public","language":[{"iso":"eng"}],"main_file_link":[{"open_access":"1","url":"https://bluefors.com/blog/integrated-quantum-measurement-system/"}],"publication_status":"published","alternative_title":["Bluefors Blog"],"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"}],"type":"other_academic_publication","citation":{"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.","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.","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.","mla":"Lake, Russell, et al. <i>The Bluefors Dilution Refrigerator as an Integrated Quantum Measurement System</i>. 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.","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."}},{"article_processing_charge":"No","keyword":["Application note"],"year":"2021","author":[{"last_name":"Simbierowicz","full_name":"Simbierowicz, Slawomir","first_name":"Slawomir"},{"first_name":"Chunyan","full_name":"Shi, Chunyan","last_name":"Shi"},{"last_name":"Collodo","full_name":"Collodo, Michele","first_name":"Michele"},{"first_name":"Moritz","full_name":"Kirste, Moritz","last_name":"Kirste"},{"id":"2AED110C-F248-11E8-B48F-1D18A9856A87","first_name":"Farid","last_name":"Hassani","full_name":"Hassani, Farid"},{"id":"4B591CBA-F248-11E8-B48F-1D18A9856A87","first_name":"Johannes M","full_name":"Fink, Johannes M","orcid":"0000-0001-8112-028X","last_name":"Fink"},{"last_name":"Bylander","full_name":"Bylander, Jonas","first_name":"Jonas"},{"first_name":"Daniel","full_name":"Perez Lozano, Daniel","last_name":"Perez Lozano"},{"first_name":"Russell","full_name":"Lake, Russell","last_name":"Lake"}],"date_published":"2021-06-03T00:00:00Z","month":"06","department":[{"_id":"JoFi"}],"date_updated":"2022-01-19T09:11:39Z","title":"Qubit energy-relaxation statistics in the Bluefors quantum measurement system","day":"03","date_created":"2022-01-19T08:41:14Z","publisher":"Bluefors Oy","_id":"10645","page":"8","oa_version":"Published Version","oa":1,"user_id":"8b945eb4-e2f2-11eb-945a-df72226e66a9","quality_controlled":"1","place":"Helsinki, Finland","status":"public","language":[{"iso":"eng"}],"main_file_link":[{"open_access":"1","url":"https://bluefors.com/blog/application-note-qubit-energy-relaxation-statistics-bluefors-quantum-measurement-system/"}],"publication_status":"published","alternative_title":["Bluefors Blog"],"abstract":[{"lang":"eng","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."}],"citation":{"ieee":"S. Simbierowicz <i>et al.</i>, <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.","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.","mla":"Simbierowicz, Slawomir, et al. <i>Qubit Energy-Relaxation Statistics in the Bluefors Quantum Measurement System</i>. Bluefors Oy, 2021.","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.","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."},"type":"other_academic_publication"},{"publication":"Physical Review B","_id":"10649","date_created":"2022-01-20T09:39:40Z","external_id":{"arxiv":["1705.08956"]},"date_updated":"2022-01-24T08:25:18Z","title":"Imaging and controlling vortex dynamics in mesoscopic superconductor-normal-metal-superconductor arrays","month":"06","date_published":"2021-06-24T00:00:00Z","article_processing_charge":"No","extern":"1","volume":103,"main_file_link":[{"open_access":"1","url":"https://arxiv.org/abs/1705.08956"}],"article_number":"224526","user_id":"8b945eb4-e2f2-11eb-945a-df72226e66a9","issue":"22","acknowledgement":"This work was supported by the Department of Energy (DOE) Basic Energy Sciences under Grant No. DE-SC0012649 and the National Science Foundation (NSF) under Grant No. DMR 17-10437. V.C. was supported by the Gordon and Betty Moore Foundation EPiQS Initiative through Grant No. GBMF4305. N.M. also acknowledges support from DOE-EFRC under Grant No. DE-SC0021238 for analysis/manuscript preparation. This research was carried out in part in the Materials Research Laboratory Central Research Facilities, University of Illinois.","oa":1,"intvolume":"       103","doi":"10.1103/physrevb.103.224526","oa_version":"Preprint","arxiv":1,"publisher":"American Physical Society","day":"24","publication_identifier":{"eissn":["2469-9969"],"issn":["2469-9950"]},"author":[{"full_name":"Naibert, Tyler R.","last_name":"Naibert","first_name":"Tyler R."},{"first_name":"Hryhoriy","id":"edfc7cb1-526e-11ec-b05a-e6ecc27e4e48","full_name":"Polshyn, Hryhoriy","orcid":"0000-0001-8223-8896","last_name":"Polshyn"},{"last_name":"Garrido-Menacho","full_name":"Garrido-Menacho, Rita","first_name":"Rita"},{"first_name":"Malcolm","full_name":"Durkin, Malcolm","last_name":"Durkin"},{"first_name":"Brian","last_name":"Wolin","full_name":"Wolin, Brian"},{"full_name":"Chua, Victor","last_name":"Chua","first_name":"Victor"},{"first_name":"Ian","full_name":"Mondragon-Shem, Ian","last_name":"Mondragon-Shem"},{"first_name":"Taylor","full_name":"Hughes, Taylor","last_name":"Hughes"},{"first_name":"Nadya","last_name":"Mason","full_name":"Mason, Nadya"},{"first_name":"Raffi","last_name":"Budakian","full_name":"Budakian, Raffi"}],"year":"2021","type":"journal_article","citation":{"ieee":"T. R. Naibert <i>et al.</i>, “Imaging and controlling vortex dynamics in mesoscopic superconductor-normal-metal-superconductor arrays,” <i>Physical Review B</i>, vol. 103, no. 22. American Physical Society, 2021.","short":"T.R. Naibert, H. Polshyn, R. Garrido-Menacho, M. Durkin, B. Wolin, V. Chua, I. Mondragon-Shem, T. Hughes, N. Mason, R. Budakian, Physical Review B 103 (2021).","apa":"Naibert, T. R., Polshyn, H., Garrido-Menacho, R., Durkin, M., Wolin, B., Chua, V., … Budakian, R. (2021). Imaging and controlling vortex dynamics in mesoscopic superconductor-normal-metal-superconductor arrays. <i>Physical Review B</i>. American Physical Society. <a href=\"https://doi.org/10.1103/physrevb.103.224526\">https://doi.org/10.1103/physrevb.103.224526</a>","ista":"Naibert TR, Polshyn H, Garrido-Menacho R, Durkin M, Wolin B, Chua V, Mondragon-Shem I, Hughes T, Mason N, Budakian R. 2021. Imaging and controlling vortex dynamics in mesoscopic superconductor-normal-metal-superconductor arrays. Physical Review B. 103(22), 224526.","mla":"Naibert, Tyler R., et al. “Imaging and Controlling Vortex Dynamics in Mesoscopic Superconductor-Normal-Metal-Superconductor Arrays.” <i>Physical Review B</i>, vol. 103, no. 22, 224526, American Physical Society, 2021, doi:<a href=\"https://doi.org/10.1103/physrevb.103.224526\">10.1103/physrevb.103.224526</a>.","ama":"Naibert TR, Polshyn H, Garrido-Menacho R, et al. Imaging and controlling vortex dynamics in mesoscopic superconductor-normal-metal-superconductor arrays. <i>Physical Review B</i>. 2021;103(22). doi:<a href=\"https://doi.org/10.1103/physrevb.103.224526\">10.1103/physrevb.103.224526</a>","chicago":"Naibert, Tyler R., Hryhoriy Polshyn, Rita Garrido-Menacho, Malcolm Durkin, Brian Wolin, Victor Chua, Ian Mondragon-Shem, Taylor Hughes, Nadya Mason, and Raffi Budakian. “Imaging and Controlling Vortex Dynamics in Mesoscopic Superconductor-Normal-Metal-Superconductor Arrays.” <i>Physical Review B</i>. American Physical Society, 2021. <a href=\"https://doi.org/10.1103/physrevb.103.224526\">https://doi.org/10.1103/physrevb.103.224526</a>."},"article_type":"original","abstract":[{"text":"Harnessing the properties of vortices in superconductors is crucial for fundamental science and technological applications; thus, it has been an ongoing goal to locally probe and control vortices. Here, we use a scanning probe technique that enables studies of vortex dynamics in superconducting systems by leveraging the resonant behavior of a raster-scanned, magnetic-tipped cantilever. This experimental setup allows us to image and control vortices, as well as extract key energy scales of the vortex interactions. Applying this technique to lattices of superconductor island arrays on a metal, we obtain a variety of striking spatial patterns that encode information about the energy landscape for vortices in the system. We interpret these patterns in terms of local vortex dynamics and extract the relative strengths of the characteristic energy scales in the system, such as the vortex-magnetic field and vortex-vortex interaction strengths, as well as the vortex chemical potential. We also demonstrate that the relative strengths of the interactions can be tuned and show how these interactions shift with an applied bias. The high degree of tunability and local nature of such vortex imaging and control not only enable new understanding of vortex interactions, but also have potential applications in more complex systems such as those relevant to quantum computing.","lang":"eng"}],"publication_status":"published","language":[{"iso":"eng"}],"status":"public","quality_controlled":"1"},{"publisher":"American Physical Society","day":"01","oa_version":"None","conference":{"end_date":"2021-03-19","start_date":"2021-03-15","location":"Virtual, United States","name":"APS: American Physical Society"},"year":"2021","author":[{"last_name":"Tschirhart","full_name":"Tschirhart, Charles","first_name":"Charles"},{"full_name":"Serlin, Marec","last_name":"Serlin","first_name":"Marec"},{"first_name":"Hryhoriy","id":"edfc7cb1-526e-11ec-b05a-e6ecc27e4e48","last_name":"Polshyn","full_name":"Polshyn, Hryhoriy","orcid":"0000-0001-8223-8896"},{"first_name":"Avi G.","last_name":"Shragai","full_name":"Shragai, Avi G."},{"first_name":"Zhengchao","last_name":"Xia","full_name":"Xia, Zhengchao"},{"full_name":"Zhu, Jiacheng","last_name":"Zhu","first_name":"Jiacheng"},{"first_name":"Yuxuan","last_name":"Zhang","full_name":"Zhang, Yuxuan"},{"full_name":"Watanabe, Kenji","last_name":"Watanabe","first_name":"Kenji"},{"first_name":"Takashi","full_name":"Taniguchi, Takashi","last_name":"Taniguchi"},{"first_name":"Martin E.","full_name":"Huber, Martin E.","last_name":"Huber"},{"last_name":"Young","full_name":"Young, Andrea","first_name":"Andrea"}],"publication_identifier":{"issn":["0003-0503"]},"citation":{"ieee":"C. Tschirhart <i>et al.</i>, “Probing orbital Chern ferromagnet phase in twisted bilayer graphene,” in <i>APS March Meeting 2021</i>, Virtual, United States, 2021, vol. 66, no. 1.","short":"C. Tschirhart, M. Serlin, H. Polshyn, A.G. Shragai, Z. Xia, J. Zhu, Y. Zhang, K. Watanabe, T. Taniguchi, M.E. Huber, A. Young, in:, APS March Meeting 2021, American Physical Society, 2021.","apa":"Tschirhart, C., Serlin, M., Polshyn, H., Shragai, A. G., Xia, Z., Zhu, J., … Young, A. (2021). Probing orbital Chern ferromagnet phase in twisted bilayer graphene. In <i>APS March Meeting 2021</i> (Vol. 66). Virtual, United States: American Physical Society.","mla":"Tschirhart, Charles, et al. “Probing Orbital Chern Ferromagnet Phase in Twisted Bilayer Graphene.” <i>APS March Meeting 2021</i>, vol. 66, no. 1, L42.00012, American Physical Society, 2021.","ista":"Tschirhart C, Serlin M, Polshyn H, Shragai AG, Xia Z, Zhu J, Zhang Y, Watanabe K, Taniguchi T, Huber ME, Young A. 2021. Probing orbital Chern ferromagnet phase in twisted bilayer graphene. APS March Meeting 2021. APS: American Physical Society, Bulletin of the American Physical Society, vol. 66, L42.00012.","chicago":"Tschirhart, Charles, Marec Serlin, Hryhoriy Polshyn, Avi G. Shragai, Zhengchao Xia, Jiacheng Zhu, Yuxuan Zhang, et al. “Probing Orbital Chern Ferromagnet Phase in Twisted Bilayer Graphene.” In <i>APS March Meeting 2021</i>, Vol. 66. American Physical Society, 2021.","ama":"Tschirhart C, Serlin M, Polshyn H, et al. Probing orbital Chern ferromagnet phase in twisted bilayer graphene. In: <i>APS March Meeting 2021</i>. Vol 66. American Physical Society; 2021."},"type":"conference","quality_controlled":"1","abstract":[{"text":"Electrons in the moiré flat bands of magic angle twisted bilayer graphene aligned to hexagonal boron nitride can break time reversal symmetry and open an interaction-driven, topological gap. The resulting magnetic order and associated quantized anomalous Hall effect have properties that diverge substantially from quantized anomalous Hall effects observed in other systems. I will present transport data and scanning probe magnetometry data acquired using a nanoSQUID-on-tip microscope. A quantitative analysis of the magnitude of the magnetization of the Chern magnet shows that the magnetic moment per moiré unit cell substantially exceeds 1 μB and grows rapidly in the topological gap, consistent with an orbital origin for the magnetic order. We find that the Barkhausen jumps observed in transport measurements can be mapped directly to microscopic motion of ferromagnetic domain walls. These domain walls are strongly pinned to disorder in the device and are reproducible across thermal cycles, suggesting coupling between the magnetic degrees of freedom and structural inhomogeneity.","lang":"eng"}],"publication_status":"published","status":"public","language":[{"iso":"eng"}],"_id":"10651","date_created":"2022-01-20T15:43:16Z","publication":"APS March Meeting 2021","article_processing_charge":"No","date_published":"2021-03-01T00:00:00Z","date_updated":"2022-01-27T09:37:51Z","title":"Probing orbital Chern ferromagnet phase in twisted bilayer graphene","month":"03","extern":"1","article_number":"L42.00012","oa":1,"intvolume":"        66","acknowledgement":"I acknowledge and appreciate support from the Hertz Foundation and from the National Science Foundation Graduate Research Fellowship Program under grant 1650114.","user_id":"8b945eb4-e2f2-11eb-945a-df72226e66a9","issue":"1","main_file_link":[{"url":"https://meetings.aps.org/Meeting/MAR21/Session/L42.12","open_access":"1"}],"alternative_title":["Bulletin of the American Physical Society"],"volume":66},{"scopus_import":"1","volume":23,"intvolume":"        23","oa":1,"user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87","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.","publication":"Molecular Therapy - Methods and Clinical Development","file_date_updated":"2022-01-24T07:43:09Z","page":"210-224","project":[{"name":"Microglia action towards neuronal circuit formation and function in health and disease","grant_number":"715571","_id":"25D4A630-B435-11E9-9278-68D0E5697425","call_identifier":"H2020"}],"_id":"10655","external_id":{"isi":["000748748500019"]},"date_created":"2022-01-23T23:01:28Z","title":"Optimizing AAV2/6 microglial targeting identified enhanced efficiency in the photoreceptor degenerative environment","date_updated":"2023-11-16T13:12:03Z","month":"12","article_processing_charge":"Yes","date_published":"2021-12-10T00:00:00Z","ec_funded":1,"file":[{"file_id":"10657","date_created":"2022-01-24T07:43:09Z","creator":"cchlebak","date_updated":"2022-01-24T07:43:09Z","content_type":"application/pdf","file_size":4794147,"relation":"main_file","checksum":"77dc540e8011c5475031bdf6ccef20a6","success":1,"access_level":"open_access","file_name":"2021_MolTherMethodsClinDev_Maes.pdf"}],"citation":{"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.","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.","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>","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>.","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.","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>."},"type":"journal_article","ddc":["570"],"acknowledged_ssus":[{"_id":"Bio"},{"_id":"LifeSc"},{"_id":"PreCl"}],"article_type":"original","abstract":[{"lang":"eng","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"}],"publication_status":"published","has_accepted_license":"1","status":"public","language":[{"iso":"eng"}],"quality_controlled":"1","doi":"10.1016/j.omtm.2021.09.006","oa_version":"Published Version","publisher":"Elsevier","day":"10","department":[{"_id":"SaSi"},{"_id":"SiHi"}],"publication_identifier":{"eissn":["2329-0501"]},"tmp":{"image":"/images/cc_by.png","short":"CC BY (4.0)","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode"},"year":"2021","isi":1,"author":[{"id":"3838F452-F248-11E8-B48F-1D18A9856A87","first_name":"Margaret E","orcid":"0000-0001-9642-1085","full_name":"Maes, Margaret E","last_name":"Maes"},{"first_name":"Gabriele M.","full_name":"Wögenstein, Gabriele M.","last_name":"Wögenstein"},{"id":"3483CF6C-F248-11E8-B48F-1D18A9856A87","first_name":"Gloria","orcid":"0000-0001-9434-8902","full_name":"Colombo, Gloria","last_name":"Colombo"},{"full_name":"Casado Polanco, Raquel","orcid":"0000-0001-8293-4568","last_name":"Casado Polanco","id":"15240fc1-dbcd-11ea-9d1d-ac5a786425fd","first_name":"Raquel"},{"orcid":"0000-0001-8635-0877","full_name":"Siegert, Sandra","last_name":"Siegert","first_name":"Sandra","id":"36ACD32E-F248-11E8-B48F-1D18A9856A87"}]},{"volume":35,"alternative_title":["Technical Tracks"],"main_file_link":[{"url":"https://ojs.aaai.org/index.php/AAAI/article/view/16496","open_access":"1"}],"related_material":{"record":[{"status":"public","relation":"dissertation_contains","id":"11362"}]},"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","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","issue":"5A","intvolume":"        35","oa":1,"scopus_import":"1","month":"05","date_updated":"2025-07-14T09:10:11Z","title":"Scalable verification of quantized neural networks","ec_funded":1,"date_published":"2021-05-28T00:00:00Z","article_processing_charge":"No","page":"3787-3795","file_date_updated":"2022-01-26T07:41:16Z","publication":"Proceedings of the AAAI Conference on Artificial Intelligence","date_created":"2022-01-25T15:15:02Z","external_id":{"arxiv":["2012.08185"]},"project":[{"grant_number":"665385","_id":"2564DBCA-B435-11E9-9278-68D0E5697425","call_identifier":"H2020","name":"International IST Doctoral Program"},{"name":"The Wittgenstein Prize","grant_number":"Z211","_id":"25F42A32-B435-11E9-9278-68D0E5697425","call_identifier":"FWF"},{"call_identifier":"H2020","grant_number":"863818","_id":"0599E47C-7A3F-11EA-A408-12923DDC885E","name":"Formal Methods for Stochastic Models: Algorithms and Applications"}],"_id":"10665","language":[{"iso":"eng"}],"status":"public","has_accepted_license":"1","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"}],"publication_status":"published","quality_controlled":"1","type":"conference","citation":{"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.","short":"T.A. Henzinger, M. Lechner, D. Zikelic, in:, Proceedings of the AAAI Conference on Artificial Intelligence, AAAI Press, 2021, pp. 3787–3795.","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.","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.","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.","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.","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."},"file":[{"file_id":"10684","date_created":"2022-01-26T07:41:16Z","creator":"mlechner","file_size":137235,"date_updated":"2022-01-26T07:41:16Z","content_type":"application/pdf","checksum":"2bc8155b2526a70fba5b7301bc89dbd1","relation":"main_file","access_level":"open_access","success":1,"file_name":"16496-Article Text-19990-1-2-20210518 (1).pdf"}],"ddc":["000"],"publication_identifier":{"issn":["2159-5399"],"eissn":["2374-3468"],"isbn":["978-1-57735-866-4"]},"department":[{"_id":"GradSch"},{"_id":"ToHe"}],"author":[{"first_name":"Thomas A","id":"40876CD8-F248-11E8-B48F-1D18A9856A87","last_name":"Henzinger","orcid":"0000-0002-2985-7724","full_name":"Henzinger, Thomas A"},{"last_name":"Lechner","full_name":"Lechner, Mathias","id":"3DC22916-F248-11E8-B48F-1D18A9856A87","first_name":"Mathias"},{"orcid":"0000-0002-4681-1699","full_name":"Zikelic, Dorde","last_name":"Zikelic","first_name":"Dorde","id":"294AA7A6-F248-11E8-B48F-1D18A9856A87"}],"conference":{"location":"Virtual","start_date":"2021-02-02","end_date":"2021-02-09","name":"AAAI: Association for the Advancement of Artificial Intelligence"},"year":"2021","oa_version":"Published Version","arxiv":1,"day":"28","publisher":"AAAI Press"},{"license":"https://creativecommons.org/licenses/by-nc-nd/3.0/","main_file_link":[{"open_access":"1","url":"https://arxiv.org/abs/2103.08187"}],"related_material":{"record":[{"id":"11362","relation":"dissertation_contains","status":"public"}]},"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).","user_id":"4359f0d1-fa6c-11eb-b949-802e58b17ae8","oa":1,"publication":"2021 IEEE International Conference on Robotics and Automation","page":"4140-4147","_id":"10666","project":[{"call_identifier":"FWF","_id":"25F42A32-B435-11E9-9278-68D0E5697425","grant_number":"Z211","name":"The Wittgenstein Prize"}],"date_created":"2022-01-25T15:44:54Z","external_id":{"isi":["000765738803040"],"arxiv":["2103.08187"]},"title":"Adversarial training is not ready for robot learning","date_updated":"2023-08-17T06:58:38Z","date_published":"2021-01-01T00:00:00Z","article_processing_charge":"No","citation":{"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>.","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>","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>","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."},"type":"conference","ddc":["000"],"abstract":[{"lang":"eng","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."}],"publication_status":"published","language":[{"iso":"eng"}],"status":"public","has_accepted_license":"1","quality_controlled":"1","doi":"10.1109/ICRA48506.2021.9561036","arxiv":1,"oa_version":"None","series_title":"ICRA","department":[{"_id":"GradSch"},{"_id":"ToHe"}],"publication_identifier":{"isbn":["978-1-7281-9078-5"],"eissn":["2577-087X"],"eisbn":["978-1-7281-9077-8"],"issn":["1050-4729"]},"tmp":{"image":"/images/cc_by_nc_nd.png","name":"Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported (CC BY-NC-ND 3.0)","legal_code_url":"https://creativecommons.org/licenses/by-nc-nd/3.0/legalcode","short":"CC BY-NC-ND (3.0)"},"isi":1,"author":[{"first_name":"Mathias","id":"3DC22916-F248-11E8-B48F-1D18A9856A87","last_name":"Lechner","full_name":"Lechner, Mathias"},{"full_name":"Hasani, Ramin","last_name":"Hasani","first_name":"Ramin"},{"full_name":"Grosu, Radu","last_name":"Grosu","first_name":"Radu"},{"first_name":"Daniela","last_name":"Rus","full_name":"Rus, Daniela"},{"id":"40876CD8-F248-11E8-B48F-1D18A9856A87","first_name":"Thomas A","last_name":"Henzinger","orcid":"0000-0002-2985-7724","full_name":"Henzinger, Thomas A"}],"conference":{"location":"Xi'an, China","start_date":"2021-05-30","end_date":"2021-06-05","name":"ICRA: International Conference on Robotics and Automation"},"year":"2021"},{"alternative_title":[" Advances in Neural Information Processing Systems"],"main_file_link":[{"url":"https://proceedings.neurips.cc/paper/2021/hash/544defa9fddff50c53b71c43e0da72be-Abstract.html","open_access":"1"}],"related_material":{"record":[{"id":"11362","relation":"dissertation_contains","status":"public"}]},"user_id":"2EBD1598-F248-11E8-B48F-1D18A9856A87","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.","oa":1,"month":"12","date_updated":"2025-07-14T09:10:12Z","title":"Infinite time horizon safety of Bayesian neural networks","ec_funded":1,"date_published":"2021-12-01T00:00:00Z","article_processing_charge":"No","file_date_updated":"2022-01-26T07:39:59Z","publication":"35th Conference on Neural Information Processing Systems","date_created":"2022-01-25T15:45:58Z","external_id":{"arxiv":["2111.03165"]},"project":[{"call_identifier":"H2020","grant_number":"665385","_id":"2564DBCA-B435-11E9-9278-68D0E5697425","name":"International IST Doctoral Program"},{"name":"Formal Methods for Stochastic Models: Algorithms and Applications","grant_number":"863818","_id":"0599E47C-7A3F-11EA-A408-12923DDC885E","call_identifier":"H2020"},{"name":"The Wittgenstein Prize","call_identifier":"FWF","grant_number":"Z211","_id":"25F42A32-B435-11E9-9278-68D0E5697425"}],"_id":"10667","language":[{"iso":"eng"}],"has_accepted_license":"1","status":"public","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"}],"publication_status":"published","quality_controlled":"1","type":"conference","citation":{"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.","short":"M. Lechner, Ð. Žikelić, K. Chatterjee, T.A. Henzinger, in:, 35th Conference on Neural Information Processing Systems, 2021.","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>","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, .","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>.","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>.","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>"},"file":[{"file_id":"10682","date_created":"2022-01-26T07:39:59Z","creator":"mlechner","checksum":"0fc0f852525c10dda9cc9ffea07fb4e4","relation":"main_file","file_size":452492,"date_updated":"2022-01-26T07:39:59Z","content_type":"application/pdf","file_name":"infinite_time_horizon_safety_o.pdf","access_level":"open_access","success":1}],"ddc":["000"],"tmp":{"image":"/images/cc_by_nc_nd.png","name":"Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported (CC BY-NC-ND 3.0)","legal_code_url":"https://creativecommons.org/licenses/by-nc-nd/3.0/legalcode","short":"CC BY-NC-ND (3.0)"},"department":[{"_id":"GradSch"},{"_id":"ToHe"},{"_id":"KrCh"}],"author":[{"id":"3DC22916-F248-11E8-B48F-1D18A9856A87","first_name":"Mathias","last_name":"Lechner","full_name":"Lechner, Mathias"},{"full_name":"Žikelić, Ðorđe","last_name":"Žikelić","first_name":"Ðorđe"},{"id":"2E5DCA20-F248-11E8-B48F-1D18A9856A87","first_name":"Krishnendu","full_name":"Chatterjee, Krishnendu","orcid":"0000-0002-4561-241X","last_name":"Chatterjee"},{"full_name":"Henzinger, Thomas A","orcid":"0000-0002-2985-7724","last_name":"Henzinger","first_name":"Thomas A","id":"40876CD8-F248-11E8-B48F-1D18A9856A87"}],"conference":{"end_date":"2021-12-10","start_date":"2021-12-06","location":"Virtual","name":"NeurIPS: Neural Information Processing Systems"},"year":"2021","arxiv":1,"oa_version":"Published Version","doi":"10.48550/arXiv.2111.03165","day":"01"},{"quality_controlled":"1","language":[{"iso":"eng"}],"has_accepted_license":"1","status":"public","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."}],"publication_status":"published","ddc":["000"],"citation":{"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.","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.","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.","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.","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.","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."},"type":"conference","file":[{"relation":"main_file","checksum":"d30eae62561bb517d9f978437d7677db","file_size":4246561,"date_updated":"2022-01-26T07:38:32Z","content_type":"application/pdf","file_name":"babaiee21a.pdf","access_level":"open_access","success":1,"file_id":"10681","creator":"mlechner","date_created":"2022-01-26T07:38:32Z"}],"author":[{"first_name":"Zahra","full_name":"Babaiee, Zahra","last_name":"Babaiee"},{"full_name":"Hasani, Ramin","last_name":"Hasani","first_name":"Ramin"},{"id":"3DC22916-F248-11E8-B48F-1D18A9856A87","first_name":"Mathias","last_name":"Lechner","full_name":"Lechner, Mathias"},{"first_name":"Daniela","full_name":"Rus, Daniela","last_name":"Rus"},{"first_name":"Radu","full_name":"Grosu, Radu","last_name":"Grosu"}],"year":"2021","conference":{"name":"ML: Machine Learning","location":"Virtual","start_date":"2021-07-18","end_date":"2021-07-24"},"tmp":{"image":"/images/cc_by_nc_nd.png","name":"Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported (CC BY-NC-ND 3.0)","legal_code_url":"https://creativecommons.org/licenses/by-nc-nd/3.0/legalcode","short":"CC BY-NC-ND (3.0)"},"publication_identifier":{"issn":["2640-3498"]},"department":[{"_id":"GradSch"},{"_id":"ToHe"}],"day":"01","publisher":"ML Research Press","oa_version":"Published Version","user_id":"2EBD1598-F248-11E8-B48F-1D18A9856A87","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).","oa":1,"intvolume":"       139","alternative_title":["PMLR"],"volume":139,"main_file_link":[{"url":"https://proceedings.mlr.press/v139/babaiee21a","open_access":"1"}],"date_published":"2021-07-01T00:00:00Z","article_processing_charge":"No","month":"07","title":"On-off center-surround receptive fields for accurate and robust image classification","date_updated":"2022-05-04T15:02:27Z","date_created":"2022-01-25T15:46:33Z","project":[{"name":"The Wittgenstein Prize","grant_number":"Z211","_id":"25F42A32-B435-11E9-9278-68D0E5697425","call_identifier":"FWF"}],"_id":"10668","page":"478-489","file_date_updated":"2022-01-26T07:38:32Z","publication":"Proceedings of the 38th International Conference on Machine Learning"},{"oa_version":"Published Version","arxiv":1,"publisher":"AAAI Press","day":"28","publication_identifier":{"isbn":["978-1-57735-866-4"],"eissn":["2374-3468"],"issn":["2159-5399"]},"department":[{"_id":"GradSch"},{"_id":"ToHe"}],"author":[{"full_name":"Grunbacher, Sophie","last_name":"Grunbacher","first_name":"Sophie"},{"first_name":"Ramin","full_name":"Hasani, Ramin","last_name":"Hasani"},{"last_name":"Lechner","full_name":"Lechner, Mathias","id":"3DC22916-F248-11E8-B48F-1D18A9856A87","first_name":"Mathias"},{"first_name":"Jacek","full_name":"Cyranka, Jacek","last_name":"Cyranka"},{"first_name":"Scott A","last_name":"Smolka","full_name":"Smolka, Scott A"},{"full_name":"Grosu, Radu","last_name":"Grosu","first_name":"Radu"}],"year":"2021","conference":{"name":"AAAI: Association for the Advancement of Artificial Intelligence","start_date":"2021-02-02","location":"Virtual","end_date":"2021-02-09"},"file":[{"file_name":"17372-Article Text-20866-1-2-20210518.pdf","success":1,"access_level":"open_access","relation":"main_file","checksum":"468d07041e282a1d46ffdae92f709630","date_updated":"2022-01-26T07:38:08Z","content_type":"application/pdf","file_size":286906,"date_created":"2022-01-26T07:38:08Z","creator":"mlechner","file_id":"10680"}],"citation":{"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.","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.","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.","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.","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.","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."},"type":"conference","ddc":["000"],"publication_status":"published","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."}],"language":[{"iso":"eng"}],"has_accepted_license":"1","status":"public","quality_controlled":"1","file_date_updated":"2022-01-26T07:38:08Z","publication":"Proceedings of the AAAI Conference on Artificial Intelligence","page":"11525-11535","project":[{"call_identifier":"FWF","_id":"25F42A32-B435-11E9-9278-68D0E5697425","grant_number":"Z211","name":"The Wittgenstein Prize"}],"_id":"10669","date_created":"2022-01-25T15:47:20Z","external_id":{"arxiv":["2012.08863"]},"date_updated":"2022-05-24T06:33:14Z","title":"On the verification of neural ODEs with stochastic guarantees","month":"05","date_published":"2021-05-28T00:00:00Z","article_processing_charge":"No","volume":35,"alternative_title":["Technical Tracks"],"main_file_link":[{"url":"https://ojs.aaai.org/index.php/AAAI/article/view/17372","open_access":"1"}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","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","issue":"13","intvolume":"        35","oa":1},{"title":"Causal navigation by continuous-time neural networks","date_updated":"2022-01-26T14:33:31Z","month":"12","article_processing_charge":"No","date_published":"2021-12-01T00:00:00Z","publication":"35th Conference on Neural Information Processing Systems","file_date_updated":"2022-01-26T07:37:24Z","_id":"10670","project":[{"call_identifier":"FWF","grant_number":"Z211","_id":"25F42A32-B435-11E9-9278-68D0E5697425","name":"The Wittgenstein Prize"}],"external_id":{"arxiv":["2106.08314"]},"date_created":"2022-01-25T15:47:50Z","main_file_link":[{"url":"https://proceedings.neurips.cc/paper/2021/hash/67ba02d73c54f0b83c05507b7fb7267f-Abstract.html","open_access":"1"}],"alternative_title":[" Advances in Neural Information Processing Systems"],"oa":1,"user_id":"8b945eb4-e2f2-11eb-945a-df72226e66a9","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","department":[{"_id":"GradSch"},{"_id":"ToHe"}],"tmp":{"image":"/images/cc_by_nc_nd.png","name":"Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported (CC BY-NC-ND 3.0)","legal_code_url":"https://creativecommons.org/licenses/by-nc-nd/3.0/legalcode","short":"CC BY-NC-ND (3.0)"},"conference":{"name":"NeurIPS: Neural Information Processing Systems","location":"Virtual","start_date":"2021-12-06","end_date":"2021-12-10"},"year":"2021","author":[{"full_name":"Vorbach, Charles J","last_name":"Vorbach","first_name":"Charles J"},{"full_name":"Hasani, Ramin","last_name":"Hasani","first_name":"Ramin"},{"last_name":"Amini","full_name":"Amini, Alexander","first_name":"Alexander"},{"full_name":"Lechner, Mathias","last_name":"Lechner","first_name":"Mathias","id":"3DC22916-F248-11E8-B48F-1D18A9856A87"},{"first_name":"Daniela","full_name":"Rus, Daniela","last_name":"Rus"}],"oa_version":"Published Version","arxiv":1,"day":"01","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"}],"publication_status":"published","status":"public","has_accepted_license":"1","language":[{"iso":"eng"}],"quality_controlled":"1","file":[{"content_type":"application/pdf","date_updated":"2022-01-26T07:37:24Z","file_size":6841228,"relation":"main_file","checksum":"be81f0ade174a8c9b2d4fe09590b2021","success":1,"access_level":"open_access","file_name":"NeurIPS-2021-causal-navigation-by-continuous-time-neural-networks-Paper.pdf","file_id":"10679","date_created":"2022-01-26T07:37:24Z","creator":"mlechner"}],"type":"conference","citation":{"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.","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.","mla":"Vorbach, Charles J., et al. “Causal Navigation by Continuous-Time Neural Networks.” <i>35th Conference on Neural Information Processing Systems</i>, 2021.","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, .","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.","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."},"ddc":["000"]},{"date_published":"2021-05-28T00:00:00Z","article_processing_charge":"No","date_updated":"2022-05-24T06:36:54Z","title":"Liquid time-constant networks","month":"05","project":[{"name":"The Wittgenstein Prize","call_identifier":"FWF","grant_number":"Z211","_id":"25F42A32-B435-11E9-9278-68D0E5697425"}],"_id":"10671","date_created":"2022-01-25T15:48:36Z","external_id":{"arxiv":["2006.04439"]},"file_date_updated":"2022-01-26T07:36:03Z","publication":"Proceedings of the AAAI Conference on Artificial Intelligence","page":"7657-7666","issue":"9","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","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.","intvolume":"        35","oa":1,"volume":35,"alternative_title":["Technical Tracks"],"main_file_link":[{"url":"https://ojs.aaai.org/index.php/AAAI/article/view/16936","open_access":"1"}],"author":[{"full_name":"Hasani, Ramin","last_name":"Hasani","first_name":"Ramin"},{"full_name":"Lechner, Mathias","last_name":"Lechner","first_name":"Mathias","id":"3DC22916-F248-11E8-B48F-1D18A9856A87"},{"first_name":"Alexander","last_name":"Amini","full_name":"Amini, Alexander"},{"last_name":"Rus","full_name":"Rus, Daniela","first_name":"Daniela"},{"full_name":"Grosu, Radu","last_name":"Grosu","first_name":"Radu"}],"conference":{"name":"AAAI: Association for the Advancement of Artificial Intelligence","location":"Virtual","start_date":"2021-02-02","end_date":"2021-02-09"},"year":"2021","department":[{"_id":"GradSch"},{"_id":"ToHe"}],"publication_identifier":{"eissn":["2374-3468"],"issn":["2159-5399"],"isbn":["978-1-57735-866-4"]},"publisher":"AAAI Press","day":"28","oa_version":"Published Version","arxiv":1,"quality_controlled":"1","publication_status":"published","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."}],"language":[{"iso":"eng"}],"has_accepted_license":"1","status":"public","ddc":["000"],"file":[{"file_id":"10678","creator":"mlechner","date_created":"2022-01-26T07:36:03Z","checksum":"0f06995fba06dbcfa7ed965fc66027ff","relation":"main_file","date_updated":"2022-01-26T07:36:03Z","content_type":"application/pdf","file_size":4302669,"file_name":"16936-Article Text-20430-1-2-20210518 (1).pdf","success":1,"access_level":"open_access"}],"citation":{"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.","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.","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.","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.","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.","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."},"type":"conference"},{"external_id":{"isi":["000658724600010"],"arxiv":["1905.03588"]},"date_created":"2022-01-25T16:32:13Z","_id":"10674","project":[{"grant_number":"M02369","_id":"264B3912-B435-11E9-9278-68D0E5697425","call_identifier":"FWF","name":"Formal Methods meets Algorithmic Game Theory"},{"call_identifier":"FWF","_id":"25F2ACDE-B435-11E9-9278-68D0E5697425","grant_number":"S11402-N23","name":"Rigorous Systems Engineering"},{"name":"The Wittgenstein Prize","_id":"25F42A32-B435-11E9-9278-68D0E5697425","grant_number":"Z211","call_identifier":"FWF"}],"page":"10:1-10:23","publication":"Logical Methods in Computer Science","file_date_updated":"2022-01-26T08:04:50Z","article_processing_charge":"No","keyword":["computer science","computer science and game theory","logic in computer science"],"date_published":"2021-02-03T00:00:00Z","month":"02","title":"Determinacy in discrete-bidding infinite-duration games","date_updated":"2023-08-17T06:56:42Z","scopus_import":"1","oa":1,"intvolume":"        17","user_id":"4359f0d1-fa6c-11eb-b949-802e58b17ae8","issue":"1","acknowledgement":"This research was supported in part by the Austrian Science Fund (FWF) under grants S11402-N23 (RiSE/SHiNE), Z211-N23 (Wittgenstein Award), and M 2369-N33 (Meitner fellowship).\r\n","volume":17,"day":"03","publisher":"International Federation for Computational Logic","oa_version":"Published Version","arxiv":1,"doi":"10.23638/LMCS-17(1:10)2021","year":"2021","author":[{"last_name":"Aghajohari","full_name":"Aghajohari, Milad","first_name":"Milad"},{"orcid":"0000-0001-5588-8287","full_name":"Avni, Guy","last_name":"Avni","first_name":"Guy","id":"463C8BC2-F248-11E8-B48F-1D18A9856A87"},{"first_name":"Thomas A","id":"40876CD8-F248-11E8-B48F-1D18A9856A87","full_name":"Henzinger, Thomas A","orcid":"0000-0002-2985-7724","last_name":"Henzinger"}],"isi":1,"tmp":{"image":"/images/cc_by.png","short":"CC BY (4.0)","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode"},"publication_identifier":{"eissn":["1860-5974"]},"department":[{"_id":"ToHe"}],"article_type":"original","ddc":["510"],"citation":{"short":"M. Aghajohari, G. Avni, T.A. Henzinger, Logical Methods in Computer Science 17 (2021) 10:1-10:23.","apa":"Aghajohari, M., Avni, G., &#38; Henzinger, T. A. (2021). Determinacy in discrete-bidding infinite-duration games. <i>Logical Methods in Computer Science</i>. International Federation for Computational Logic. <a href=\"https://doi.org/10.23638/LMCS-17(1:10)2021\">https://doi.org/10.23638/LMCS-17(1:10)2021</a>","ieee":"M. Aghajohari, G. Avni, and T. A. Henzinger, “Determinacy in discrete-bidding infinite-duration games,” <i>Logical Methods in Computer Science</i>, vol. 17, no. 1. International Federation for Computational Logic, p. 10:1-10:23, 2021.","chicago":"Aghajohari, Milad, Guy Avni, and Thomas A Henzinger. “Determinacy in Discrete-Bidding Infinite-Duration Games.” <i>Logical Methods in Computer Science</i>. International Federation for Computational Logic, 2021. <a href=\"https://doi.org/10.23638/LMCS-17(1:10)2021\">https://doi.org/10.23638/LMCS-17(1:10)2021</a>.","ama":"Aghajohari M, Avni G, Henzinger TA. Determinacy in discrete-bidding infinite-duration games. <i>Logical Methods in Computer Science</i>. 2021;17(1):10:1-10:23. doi:<a href=\"https://doi.org/10.23638/LMCS-17(1:10)2021\">10.23638/LMCS-17(1:10)2021</a>","mla":"Aghajohari, Milad, et al. “Determinacy in Discrete-Bidding Infinite-Duration Games.” <i>Logical Methods in Computer Science</i>, vol. 17, no. 1, International Federation for Computational Logic, 2021, p. 10:1-10:23, doi:<a href=\"https://doi.org/10.23638/LMCS-17(1:10)2021\">10.23638/LMCS-17(1:10)2021</a>.","ista":"Aghajohari M, Avni G, Henzinger TA. 2021. Determinacy in discrete-bidding infinite-duration games. Logical Methods in Computer Science. 17(1), 10:1-10:23."},"type":"journal_article","file":[{"file_id":"10690","creator":"alisjak","date_created":"2022-01-26T08:04:50Z","relation":"main_file","checksum":"b35586a50ed1ca8f44767de116d18d81","file_size":819878,"date_updated":"2022-01-26T08:04:50Z","content_type":"application/pdf","file_name":"2021_LMCS_AGHAJOHAR.pdf","access_level":"open_access","success":1}],"quality_controlled":"1","has_accepted_license":"1","status":"public","language":[{"iso":"eng"}],"abstract":[{"lang":"eng","text":"In two-player games on graphs, the players move a token through a graph to produce an infinite path, which determines the winner of the game. Such games are central in formal methods since they model the interaction between a non-terminating system and its environment. In bidding games the players bid for the right to move the token: in each round, the players simultaneously submit bids, and the higher bidder moves the token and pays the other player. Bidding games are known to have a clean and elegant mathematical structure that relies on the ability of the players to submit arbitrarily small bids. Many applications, however, require a fixed granularity for the bids, which can represent, for example, the monetary value expressed in cents. We study, for the first time, the combination of discrete-bidding and infinite-duration games. Our most important result proves that these games form a large determined subclass of concurrent games, where determinacy is the strong property that there always exists exactly one player who can guarantee winning the game. In particular, we show that, in contrast to non-discrete bidding games, the mechanism with which tied bids are resolved plays an important role in discrete-bidding games. We study several natural tie-breaking mechanisms and show that, while some do not admit determinacy, most natural mechanisms imply determinacy for every pair of initial budgets."}],"publication_status":"published"},{"file":[{"date_created":"2022-01-26T08:04:29Z","creator":"cchlebak","file_id":"10689","success":1,"access_level":"open_access","file_name":"2021_FCAD2021_Kragl.pdf","content_type":"application/pdf","date_updated":"2022-01-26T08:04:29Z","file_size":390555,"checksum":"35438ac9f9750340b7f8ae4ae3220d9f","relation":"main_file"}],"citation":{"ieee":"B. Kragl and S. Qadeer, “The Civl verifier,” in <i>Proceedings of the 21st Conference on Formal Methods in Computer-Aided Design</i>, Virtual, 2021, vol. 2, pp. 143–152.","short":"B. Kragl, S. Qadeer, in:, P. Ruzica, M.W. Whalen (Eds.), Proceedings of the 21st Conference on Formal Methods in Computer-Aided Design, TU Wien Academic Press, 2021, pp. 143–152.","apa":"Kragl, B., &#38; Qadeer, S. (2021). The Civl verifier. In P. Ruzica &#38; M. W. Whalen (Eds.), <i>Proceedings of the 21st Conference on Formal Methods in Computer-Aided Design</i> (Vol. 2, pp. 143–152). Virtual: TU Wien Academic Press. <a href=\"https://doi.org/10.34727/2021/isbn.978-3-85448-046-4_23\">https://doi.org/10.34727/2021/isbn.978-3-85448-046-4_23</a>","ista":"Kragl B, Qadeer S. 2021. The Civl verifier. Proceedings of the 21st Conference on Formal Methods in Computer-Aided Design. FMCAD: Formal Methods in Computer-Aided Design, Conference Series, vol. 2, 143–152.","mla":"Kragl, Bernhard, and Shaz Qadeer. “The Civl Verifier.” <i>Proceedings of the 21st Conference on Formal Methods in Computer-Aided Design</i>, edited by Piskac Ruzica and Michael W. Whalen, vol. 2, TU Wien Academic Press, 2021, pp. 143–152, doi:<a href=\"https://doi.org/10.34727/2021/isbn.978-3-85448-046-4_23\">10.34727/2021/isbn.978-3-85448-046-4_23</a>.","ama":"Kragl B, Qadeer S. The Civl verifier. In: Ruzica P, Whalen MW, eds. <i>Proceedings of the 21st Conference on Formal Methods in Computer-Aided Design</i>. Vol 2. TU Wien Academic Press; 2021:143–152. doi:<a href=\"https://doi.org/10.34727/2021/isbn.978-3-85448-046-4_23\">10.34727/2021/isbn.978-3-85448-046-4_23</a>","chicago":"Kragl, Bernhard, and Shaz Qadeer. “The Civl Verifier.” In <i>Proceedings of the 21st Conference on Formal Methods in Computer-Aided Design</i>, edited by Piskac Ruzica and Michael W. Whalen, 2:143–152. TU Wien Academic Press, 2021. <a href=\"https://doi.org/10.34727/2021/isbn.978-3-85448-046-4_23\">https://doi.org/10.34727/2021/isbn.978-3-85448-046-4_23</a>."},"type":"conference","ddc":["000"],"publication_status":"published","abstract":[{"text":"Civl is a static verifier for concurrent programs designed around the conceptual framework of layered refinement,\r\nwhich views the task of verifying a program as a sequence of program simplification steps each justified by its own invariant. Civl verifies a layered concurrent program that compactly expresses all the programs in this sequence and the supporting invariants. This paper presents the design and implementation of the Civl verifier.","lang":"eng"}],"language":[{"iso":"eng"}],"status":"public","has_accepted_license":"1","quality_controlled":"1","doi":"10.34727/2021/isbn.978-3-85448-046-4_23","oa_version":"Published Version","publisher":"TU Wien Academic Press","day":"01","publication_identifier":{"isbn":["978-3-85448-046-4"]},"department":[{"_id":"ToHe"}],"tmp":{"image":"/images/cc_by.png","short":"CC BY (4.0)","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode"},"author":[{"last_name":"Kragl","full_name":"Kragl, Bernhard","orcid":"0000-0001-7745-9117","first_name":"Bernhard","id":"320FC952-F248-11E8-B48F-1D18A9856A87"},{"first_name":"Shaz","last_name":"Qadeer","full_name":"Qadeer, Shaz"}],"year":"2021","conference":{"end_date":"2021-10-22","start_date":"2021-10-20","location":"Virtual","name":"FMCAD: Formal Methods in Computer-Aided Design"},"editor":[{"first_name":"Piskac","last_name":"Ruzica","full_name":"Ruzica, Piskac"},{"first_name":"Michael W.","last_name":"Whalen","full_name":"Whalen, Michael W."}],"alternative_title":["Conference Series"],"volume":2,"acknowledgement":"This research was performed while Bernhard Kragl was at IST Austria, supported in part by the Austrian Science Fund (FWF) under grant Z211-N23 (Wittgenstein Award).","user_id":"8b945eb4-e2f2-11eb-945a-df72226e66a9","oa":1,"intvolume":"         2","file_date_updated":"2022-01-26T08:04:29Z","publication":"Proceedings of the 21st Conference on Formal Methods in Computer-Aided Design","page":"143–152","project":[{"_id":"25F42A32-B435-11E9-9278-68D0E5697425","grant_number":"Z211","call_identifier":"FWF","name":"The Wittgenstein Prize"}],"_id":"10688","date_created":"2022-01-26T08:01:30Z","title":"The Civl verifier","date_updated":"2022-01-26T08:20:41Z","month":"10","date_published":"2021-10-01T00:00:00Z","article_processing_charge":"No"},{"article_number":"E42.00010","quality_controlled":"1","issue":"1","user_id":"8b945eb4-e2f2-11eb-945a-df72226e66a9","oa":1,"intvolume":"        66","abstract":[{"text":"We experimentally investigate narrow and topologically nontrivial moiré minibands hosted by van der Waals heterostructures consisting of a graphene monolayer rotationally faulted with respect to a Bernal-stacked bilayer. At fillings ν= 1 and 3 electrons per moiré unit cell within these bands, we observe quantized anomalous Hall effects with Rxy≈h/2e2, indicative of spontaneous polarization of the system into a single valley-projected band with Chern number C= 2. Remarkably, we also observe the evidence of symmetry broken Chern insulator states at ν= 1.5 and 3.5. At ν= 3 we find that the sign of the quantum anomalous Hall effect can be reversed via field-effect control of the chemical potential. This curious effect arises from the magnetization contribution due to topological edge states, which drive a reversal of the total magnetization and thus a switch of the favored magnetic state. Remarkably, we find that this switch is hysteretic, which we use to demonstrate non-volatile electric-field-induced reversal of the magnetic state. Voltage control of magnetic states can be used to electrically pattern nonvolatile magnetic domain structures hosting chiral edge states, with applications ranging from reconfigurable microwave circuit elements to ultra-low-power magnetic memory.","lang":"eng"}],"volume":66,"alternative_title":["Bulletin of the American Physical Society"],"main_file_link":[{"url":"https://meetings.aps.org/Meeting/MAR21/Session/E42.10","open_access":"1"}],"language":[{"iso":"eng"}],"status":"public","citation":{"mla":"Polshyn, Hryhoriy, et al. “Orbital Chern Insulator States in Twisted Monolayer-Bilayer Graphene and Electrical Switching of Topological and Magnetic Order.” <i>APS March Meeting 2021</i>, vol. 66, no. 1, E42.00010, American Physical Society, 2021.","ista":"Polshyn H, Zhu J, Kumar M, Zhang Y, Yang F, Tschirhart C, Serlin M, Watanabe K, Tanaguchi T, MacDonald A, Young A. 2021. Orbital Chern insulator states in twisted monolayer-bilayer graphene and electrical switching of topological and magnetic order. APS March Meeting 2021. APS: American Physical Society, Bulletin of the American Physical Society, vol. 66, E42.00010.","chicago":"Polshyn, Hryhoriy, Jihang Zhu, Manish Kumar, Yuxuan Zhang, Fangyuan Yang, Charles Tschirhart, Marec Serlin, et al. “Orbital Chern Insulator States in Twisted Monolayer-Bilayer Graphene and Electrical Switching of Topological and Magnetic Order.” In <i>APS March Meeting 2021</i>, Vol. 66. American Physical Society, 2021.","ama":"Polshyn H, Zhu J, Kumar M, et al. Orbital Chern insulator states in twisted monolayer-bilayer graphene and electrical switching of topological and magnetic order. In: <i>APS March Meeting 2021</i>. Vol 66. American Physical Society; 2021.","ieee":"H. Polshyn <i>et al.</i>, “Orbital Chern insulator states in twisted monolayer-bilayer graphene and electrical switching of topological and magnetic order,” in <i>APS March Meeting 2021</i>, Virtual, 2021, vol. 66, no. 1.","apa":"Polshyn, H., Zhu, J., Kumar, M., Zhang, Y., Yang, F., Tschirhart, C., … Young, A. (2021). Orbital Chern insulator states in twisted monolayer-bilayer graphene and electrical switching of topological and magnetic order. In <i>APS March Meeting 2021</i> (Vol. 66). Virtual: American Physical Society.","short":"H. Polshyn, J. Zhu, M. Kumar, Y. Zhang, F. Yang, C. Tschirhart, M. Serlin, K. Watanabe, T. Tanaguchi, A. MacDonald, A. Young, in:, APS March Meeting 2021, American Physical Society, 2021."},"type":"conference","extern":"1","date_published":"2021-03-01T00:00:00Z","author":[{"orcid":"0000-0001-8223-8896","full_name":"Polshyn, Hryhoriy","last_name":"Polshyn","id":"edfc7cb1-526e-11ec-b05a-e6ecc27e4e48","first_name":"Hryhoriy"},{"first_name":"Jihang","full_name":"Zhu, Jihang","last_name":"Zhu"},{"first_name":"Manish","full_name":"Kumar, Manish","last_name":"Kumar"},{"first_name":"Yuxuan","last_name":"Zhang","full_name":"Zhang, Yuxuan"},{"last_name":"Yang","full_name":"Yang, Fangyuan","first_name":"Fangyuan"},{"first_name":"Charles","last_name":"Tschirhart","full_name":"Tschirhart, Charles"},{"last_name":"Serlin","full_name":"Serlin, Marec","first_name":"Marec"},{"first_name":"Kenji","last_name":"Watanabe","full_name":"Watanabe, Kenji"},{"full_name":"Tanaguchi, Takashi","last_name":"Tanaguchi","first_name":"Takashi"},{"first_name":"Allan","last_name":"MacDonald","full_name":"MacDonald, Allan"},{"full_name":"Young, Andrea","last_name":"Young","first_name":"Andrea"}],"article_processing_charge":"No","year":"2021","conference":{"name":"APS: American Physical Society","location":"Virtual","start_date":"2021-03-15","end_date":"2021-03-19"},"date_updated":"2022-01-27T10:46:23Z","title":"Orbital Chern insulator states in twisted monolayer-bilayer graphene and electrical switching of topological and magnetic order","publication_identifier":{"issn":["0003-0503"]},"month":"03","publisher":"American Physical Society","_id":"10692","date_created":"2022-01-27T09:49:48Z","day":"01","publication":"APS March Meeting 2021","oa_version":"Published Version"},{"scopus_import":"1","oa":1,"user_id":"8b945eb4-e2f2-11eb-945a-df72226e66a9","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 by the European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie Grant Agreement No. 665385.","main_file_link":[{"open_access":"1","url":"https://arxiv.org/abs/2005.06636"}],"external_id":{"arxiv":["2005.06636"]},"date_created":"2022-01-27T12:11:23Z","_id":"10694","project":[{"_id":"25F42A32-B435-11E9-9278-68D0E5697425","grant_number":"Z211","call_identifier":"FWF","name":"The Wittgenstein Prize"},{"_id":"0599E47C-7A3F-11EA-A408-12923DDC885E","grant_number":"863818","call_identifier":"H2020","name":"Formal Methods for Stochastic Models: Algorithms and Applications"},{"grant_number":"665385","_id":"2564DBCA-B435-11E9-9278-68D0E5697425","call_identifier":"H2020","name":"International IST Doctoral Program"}],"page":"617-636","publication":"Proceedings of the 2021 ACM-SIAM Symposium on Discrete Algorithms","ec_funded":1,"article_processing_charge":"No","date_published":"2021-01-01T00:00:00Z","month":"01","date_updated":"2025-07-14T09:10:12Z","title":"Infinite-duration all-pay bidding games","citation":{"short":"G. Avni, I.R. Jecker, D. Zikelic, in:, D. Marx (Ed.), Proceedings of the 2021 ACM-SIAM Symposium on Discrete Algorithms, Society for Industrial and Applied Mathematics, 2021, pp. 617–636.","apa":"Avni, G., Jecker, I. R., &#38; Zikelic, D. (2021). Infinite-duration all-pay bidding games. In D. Marx (Ed.), <i>Proceedings of the 2021 ACM-SIAM Symposium on Discrete Algorithms</i> (pp. 617–636). Virtual: Society for Industrial and Applied Mathematics. <a href=\"https://doi.org/10.1137/1.9781611976465.38\">https://doi.org/10.1137/1.9781611976465.38</a>","ieee":"G. Avni, I. R. Jecker, and D. Zikelic, “Infinite-duration all-pay bidding games,” in <i>Proceedings of the 2021 ACM-SIAM Symposium on Discrete Algorithms</i>, Virtual, 2021, pp. 617–636.","ama":"Avni G, Jecker IR, Zikelic D. Infinite-duration all-pay bidding games. In: Marx D, ed. <i>Proceedings of the 2021 ACM-SIAM Symposium on Discrete Algorithms</i>. Society for Industrial and Applied Mathematics; 2021:617-636. doi:<a href=\"https://doi.org/10.1137/1.9781611976465.38\">10.1137/1.9781611976465.38</a>","chicago":"Avni, Guy, Ismael R Jecker, and Dorde Zikelic. “Infinite-Duration All-Pay Bidding Games.” In <i>Proceedings of the 2021 ACM-SIAM Symposium on Discrete Algorithms</i>, edited by Dániel Marx, 617–36. Society for Industrial and Applied Mathematics, 2021. <a href=\"https://doi.org/10.1137/1.9781611976465.38\">https://doi.org/10.1137/1.9781611976465.38</a>.","ista":"Avni G, Jecker IR, Zikelic D. 2021. Infinite-duration all-pay bidding games. Proceedings of the 2021 ACM-SIAM Symposium on Discrete Algorithms. SODA: Symposium on Discrete Algorithms, 617–636.","mla":"Avni, Guy, et al. “Infinite-Duration All-Pay Bidding Games.” <i>Proceedings of the 2021 ACM-SIAM Symposium on Discrete Algorithms</i>, edited by Dániel Marx, Society for Industrial and Applied Mathematics, 2021, pp. 617–36, doi:<a href=\"https://doi.org/10.1137/1.9781611976465.38\">10.1137/1.9781611976465.38</a>."},"type":"conference","quality_controlled":"1","status":"public","language":[{"iso":"eng"}],"abstract":[{"lang":"eng","text":"In a two-player zero-sum graph game the players move a token throughout a graph to produce an infinite path, which determines the winner or payoff of the game. Traditionally, the players alternate turns in moving the token. In bidding games, however, the players have budgets, and in each turn, we hold an “auction” (bidding) to determine which player moves the token: both players simultaneously submit bids and the higher bidder moves the token. The bidding mechanisms differ in their payment schemes. Bidding games were largely studied with variants of first-price bidding in which only the higher bidder pays his bid. We focus on all-pay bidding, where both players pay their bids. Finite-duration all-pay bidding games were studied and shown to be technically more challenging than their first-price counterparts. We study for the first time, infinite-duration all-pay bidding games. Our most interesting results are for mean-payoff objectives: we portray a complete picture for games played on strongly-connected graphs. We study both pure (deterministic) and mixed (probabilistic) strategies and completely characterize the optimal and almost-sure (with probability 1) payoffs the players can respectively guarantee. We show that mean-payoff games under all-pay bidding exhibit the intriguing mathematical properties of their first-price counterparts; namely, an equivalence with random-turn games in which in each turn, the player who moves is selected according to a (biased) coin toss. The equivalences for all-pay bidding are more intricate and unexpected than for first-price bidding."}],"publication_status":"published","day":"01","publisher":"Society for Industrial and Applied Mathematics","oa_version":"Preprint","arxiv":1,"doi":"10.1137/1.9781611976465.38","editor":[{"last_name":"Marx","full_name":"Marx, Dániel","first_name":"Dániel"}],"year":"2021","conference":{"name":"SODA: Symposium on Discrete Algorithms","end_date":"2021-01-13","start_date":"2021-01-10","location":"Virtual"},"author":[{"first_name":"Guy","id":"463C8BC2-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0001-5588-8287","full_name":"Avni, Guy","last_name":"Avni"},{"id":"85D7C63E-7D5D-11E9-9C0F-98C4E5697425","first_name":"Ismael R","full_name":"Jecker, Ismael R","last_name":"Jecker"},{"first_name":"Dorde","id":"294AA7A6-F248-11E8-B48F-1D18A9856A87","full_name":"Zikelic, Dorde","orcid":"0000-0002-4681-1699","last_name":"Zikelic"}],"publication_identifier":{"isbn":["978-1-61197-646-5"]},"department":[{"_id":"GradSch"},{"_id":"KrCh"}]},{"main_file_link":[{"url":"https://arxiv.org/abs/1909.03266","open_access":"1"}],"volume":157,"intvolume":"       157","oa":1,"issue":"7","user_id":"4359f0d1-fa6c-11eb-b949-802e58b17ae8","acknowledgement":"We would like to thank the anonymous referees for carefully reading the paper and for their remarks and suggestions.","publication":"Compositio Mathematica","page":"1610-1651","_id":"10711","external_id":{"isi":["000667289300001"],"arxiv":["1909.03266"]},"date_created":"2022-02-01T08:10:43Z","title":"The distribution of the maximum of partial sums of Kloosterman sums and other trace functions","date_updated":"2023-08-17T06:59:16Z","month":"06","keyword":["Algebra and Number Theory"],"article_processing_charge":"No","date_published":"2021-06-28T00:00:00Z","citation":{"apa":"Autissier, P., Bonolis, D., &#38; Lamzouri, Y. (2021). The distribution of the maximum of partial sums of Kloosterman sums and other trace functions. <i>Compositio Mathematica</i>. Cambridge University Press. <a href=\"https://doi.org/10.1112/s0010437x21007351\">https://doi.org/10.1112/s0010437x21007351</a>","short":"P. Autissier, D. Bonolis, Y. Lamzouri, Compositio Mathematica 157 (2021) 1610–1651.","ieee":"P. Autissier, D. Bonolis, and Y. Lamzouri, “The distribution of the maximum of partial sums of Kloosterman sums and other trace functions,” <i>Compositio Mathematica</i>, vol. 157, no. 7. Cambridge University Press, pp. 1610–1651, 2021.","chicago":"Autissier, Pascal, Dante Bonolis, and Youness Lamzouri. “The Distribution of the Maximum of Partial Sums of Kloosterman Sums and Other Trace Functions.” <i>Compositio Mathematica</i>. Cambridge University Press, 2021. <a href=\"https://doi.org/10.1112/s0010437x21007351\">https://doi.org/10.1112/s0010437x21007351</a>.","ama":"Autissier P, Bonolis D, Lamzouri Y. The distribution of the maximum of partial sums of Kloosterman sums and other trace functions. <i>Compositio Mathematica</i>. 2021;157(7):1610-1651. doi:<a href=\"https://doi.org/10.1112/s0010437x21007351\">10.1112/s0010437x21007351</a>","mla":"Autissier, Pascal, et al. “The Distribution of the Maximum of Partial Sums of Kloosterman Sums and Other Trace Functions.” <i>Compositio Mathematica</i>, vol. 157, no. 7, Cambridge University Press, 2021, pp. 1610–51, doi:<a href=\"https://doi.org/10.1112/s0010437x21007351\">10.1112/s0010437x21007351</a>.","ista":"Autissier P, Bonolis D, Lamzouri Y. 2021. The distribution of the maximum of partial sums of Kloosterman sums and other trace functions. Compositio Mathematica. 157(7), 1610–1651."},"type":"journal_article","article_type":"original","publication_status":"published","abstract":[{"text":"In this paper, we investigate the distribution of the maximum of partial sums of families of  m -periodic complex-valued functions satisfying certain conditions. We obtain precise uniform estimates for the distribution function of this maximum in a near-optimal range. Our results apply to partial sums of Kloosterman sums and other families of  ℓ -adic trace functions, and are as strong as those obtained by Bober, Goldmakher, Granville and Koukoulopoulos for character sums. In particular, we improve on the recent work of the third author for Birch sums. However, unlike character sums, we are able to construct families of  m -periodic complex-valued functions which satisfy our conditions, but for which the Pólya–Vinogradov inequality is sharp.","lang":"eng"}],"status":"public","language":[{"iso":"eng"}],"quality_controlled":"1","doi":"10.1112/s0010437x21007351","arxiv":1,"oa_version":"Preprint","publisher":"Cambridge University Press","day":"28","publication_identifier":{"eissn":["1570-5846"],"issn":["0010-437X"]},"department":[{"_id":"TiBr"}],"year":"2021","author":[{"first_name":"Pascal","last_name":"Autissier","full_name":"Autissier, Pascal"},{"full_name":"Bonolis, Dante","last_name":"Bonolis","first_name":"Dante","id":"6A459894-5FDD-11E9-AF35-BB24E6697425"},{"first_name":"Youness","last_name":"Lamzouri","full_name":"Lamzouri, Youness"}],"isi":1},{"main_file_link":[{"open_access":"1","url":"https://arxiv.org/abs/1904.12532"}],"volume":14,"oa":1,"intvolume":"        14","acknowledgement":"N. L. and R. S. gratefully acknowledge financial support by the European Research Council\r\n(ERC) under the European Union’s Horizon 2020 research and innovation programme (grant\r\nagreement No 694227). B. S. acknowledges support from the Swiss National Science Foundation (grant 200020_172623) and from the NCCR SwissMAP. N. L. would like to thank\r\nAndreas Deuchert and David Mitrouskas for interesting discussions. B. S. and R. S. would\r\nlike to thank Rupert Frank for stimulating discussions about the time-evolution of a polaron.\r\n","issue":"7","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","scopus_import":"1","month":"11","title":" The Landau–Pekar equations: Adiabatic theorem and accuracy","date_updated":"2023-10-17T11:26:45Z","ec_funded":1,"article_processing_charge":"No","date_published":"2021-11-10T00:00:00Z","page":"2079-2100","publication":"Analysis and PDE","external_id":{"arxiv":["1904.12532"],"isi":["000733976600004"]},"date_created":"2022-02-06T23:01:33Z","project":[{"call_identifier":"H2020","_id":"25C6DC12-B435-11E9-9278-68D0E5697425","grant_number":"694227","name":"Analysis of quantum many-body systems"}],"_id":"10738","status":"public","language":[{"iso":"eng"}],"publication_status":"published","abstract":[{"text":"We prove an adiabatic theorem for the Landau–Pekar equations. This allows us to derive new results on the accuracy of their use as effective equations for the time evolution generated by the Fröhlich Hamiltonian with large coupling constant α. In particular, we show that the time evolution of Pekar product states with coherent phonon field and the electron being trapped by the phonons is well approximated by the Landau–Pekar equations until times short compared to α2.","lang":"eng"}],"quality_controlled":"1","citation":{"chicago":"Leopold, Nikolai K, Simone Anna Elvira Rademacher, Benjamin Schlein, and Robert Seiringer. “ The Landau–Pekar Equations: Adiabatic Theorem and Accuracy.” <i>Analysis and PDE</i>. Mathematical Sciences Publishers, 2021. <a href=\"https://doi.org/10.2140/APDE.2021.14.2079\">https://doi.org/10.2140/APDE.2021.14.2079</a>.","ama":"Leopold NK, Rademacher SAE, Schlein B, Seiringer R.  The Landau–Pekar equations: Adiabatic theorem and accuracy. <i>Analysis and PDE</i>. 2021;14(7):2079-2100. doi:<a href=\"https://doi.org/10.2140/APDE.2021.14.2079\">10.2140/APDE.2021.14.2079</a>","ista":"Leopold NK, Rademacher SAE, Schlein B, Seiringer R. 2021.  The Landau–Pekar equations: Adiabatic theorem and accuracy. Analysis and PDE. 14(7), 2079–2100.","mla":"Leopold, Nikolai K., et al. “ The Landau–Pekar Equations: Adiabatic Theorem and Accuracy.” <i>Analysis and PDE</i>, vol. 14, no. 7, Mathematical Sciences Publishers, 2021, pp. 2079–100, doi:<a href=\"https://doi.org/10.2140/APDE.2021.14.2079\">10.2140/APDE.2021.14.2079</a>.","short":"N.K. Leopold, S.A.E. Rademacher, B. Schlein, R. Seiringer, Analysis and PDE 14 (2021) 2079–2100.","apa":"Leopold, N. K., Rademacher, S. A. E., Schlein, B., &#38; Seiringer, R. (2021).  The Landau–Pekar equations: Adiabatic theorem and accuracy. <i>Analysis and PDE</i>. Mathematical Sciences Publishers. <a href=\"https://doi.org/10.2140/APDE.2021.14.2079\">https://doi.org/10.2140/APDE.2021.14.2079</a>","ieee":"N. K. Leopold, S. A. E. Rademacher, B. Schlein, and R. Seiringer, “ The Landau–Pekar equations: Adiabatic theorem and accuracy,” <i>Analysis and PDE</i>, vol. 14, no. 7. Mathematical Sciences Publishers, pp. 2079–2100, 2021."},"type":"journal_article","article_type":"original","department":[{"_id":"RoSe"}],"publication_identifier":{"issn":["2157-5045"],"eissn":["1948-206X"]},"year":"2021","isi":1,"author":[{"last_name":"Leopold","orcid":"0000-0002-0495-6822","full_name":"Leopold, Nikolai K","first_name":"Nikolai K","id":"4BC40BEC-F248-11E8-B48F-1D18A9856A87"},{"last_name":"Rademacher","orcid":"0000-0001-5059-4466","full_name":"Rademacher, Simone Anna Elvira","id":"856966FE-A408-11E9-977E-802DE6697425","first_name":"Simone Anna Elvira"},{"first_name":"Benjamin","last_name":"Schlein","full_name":"Schlein, Benjamin"},{"full_name":"Seiringer, Robert","orcid":"0000-0002-6781-0521","last_name":"Seiringer","first_name":"Robert","id":"4AFD0470-F248-11E8-B48F-1D18A9856A87"}],"arxiv":1,"oa_version":"Preprint","doi":"10.2140/APDE.2021.14.2079","day":"10","publisher":"Mathematical Sciences Publishers"},{"type":"preprint","citation":{"mla":"Rzadkowski, Wojciech, et al. “Artificial Neural Network States for Non-Additive Systems.” <i>ArXiv</i>, doi:<a href=\"https://doi.org/10.48550/arXiv.2105.15193\">10.48550/arXiv.2105.15193</a>.","ista":"Rzadkowski W, Lemeshko M, Mentink JH. Artificial neural network states for non-additive systems. arXiv, <a href=\"https://doi.org/10.48550/arXiv.2105.15193\">10.48550/arXiv.2105.15193</a>.","ama":"Rzadkowski W, Lemeshko M, Mentink JH. Artificial neural network states for non-additive systems. <i>arXiv</i>. doi:<a href=\"https://doi.org/10.48550/arXiv.2105.15193\">10.48550/arXiv.2105.15193</a>","chicago":"Rzadkowski, Wojciech, Mikhail Lemeshko, and Johan H. Mentink. “Artificial Neural Network States for Non-Additive Systems.” <i>ArXiv</i>, n.d. <a href=\"https://doi.org/10.48550/arXiv.2105.15193\">https://doi.org/10.48550/arXiv.2105.15193</a>.","ieee":"W. Rzadkowski, M. Lemeshko, and J. H. Mentink, “Artificial neural network states for non-additive systems,” <i>arXiv</i>. .","short":"W. Rzadkowski, M. Lemeshko, J.H. Mentink, ArXiv (n.d.).","apa":"Rzadkowski, W., Lemeshko, M., &#38; Mentink, J. H. (n.d.). Artificial neural network states for non-additive systems. <i>arXiv</i>. <a href=\"https://doi.org/10.48550/arXiv.2105.15193\">https://doi.org/10.48550/arXiv.2105.15193</a>"},"status":"public","language":[{"iso":"eng"}],"main_file_link":[{"open_access":"1","url":"https://arxiv.org/abs/2105.15193"}],"related_material":{"record":[{"id":"10759","status":"public","relation":"dissertation_contains"}]},"publication_status":"submitted","abstract":[{"text":"Methods inspired from machine learning have recently attracted great interest in the computational study of quantum many-particle systems. So far, however, it has proven challenging to deal with microscopic models in which the total number of particles is not conserved. To address this issue, we propose a new variant of neural network states, which we term neural coherent states. Taking the Fröhlich impurity model as a case study, we show that neural coherent states can learn the ground state of non-additive systems very well. In particular, we observe substantial improvement over the standard coherent state estimates in the most challenging intermediate coupling regime. Our approach is generic and does not assume specific details of the system, suggesting wide applications.","lang":"eng"}],"oa":1,"acknowledgement":"We acknowledge fruitful discussions with Giacomo Bighin, Giammarco Fabiani, Areg Ghazaryan, Christoph\r\nLampert, and Artem Volosniev at various stages of this work. W.R. is a recipient of a DOC Fellowship of the\r\nAustrian Academy of Sciences and has received funding from the EU Horizon 2020 programme under the Marie\r\nSkłodowska-Curie Grant Agreement No. 665385. M. L. acknowledges support by the European Research Council (ERC) Starting Grant No. 801770 (ANGULON). This work is part of the Shell-NWO/FOM-initiative “Computational sciences for energy research” of Shell and Chemical Sciences, Earth and Life Sciences, Physical Sciences, FOM and STW.","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","page":"2105.15193","oa_version":"Preprint","arxiv":1,"doi":"10.48550/arXiv.2105.15193","publication":"arXiv","day":"31","external_id":{"arxiv":["2105.15193"]},"date_created":"2022-02-17T11:18:57Z","_id":"10762","project":[{"name":"Angulon: physics and applications of a new quasiparticle","_id":"2688CF98-B435-11E9-9278-68D0E5697425","grant_number":"801770","call_identifier":"H2020"},{"name":"International IST Doctoral Program","_id":"2564DBCA-B435-11E9-9278-68D0E5697425","grant_number":"665385","call_identifier":"H2020"}],"month":"05","department":[{"_id":"MiLe"}],"title":"Artificial neural network states for non-additive systems","date_updated":"2023-09-07T13:44:16Z","ec_funded":1,"article_processing_charge":"No","year":"2021","author":[{"id":"48C55298-F248-11E8-B48F-1D18A9856A87","first_name":"Wojciech","last_name":"Rzadkowski","orcid":"0000-0002-1106-4419","full_name":"Rzadkowski, Wojciech"},{"full_name":"Lemeshko, Mikhail","orcid":"0000-0002-6990-7802","last_name":"Lemeshko","id":"37CB05FA-F248-11E8-B48F-1D18A9856A87","first_name":"Mikhail"},{"last_name":"Mentink","full_name":"Mentink, Johan H.","first_name":"Johan H."}],"date_published":"2021-05-31T00:00:00Z"},{"related_material":{"record":[{"relation":"dissertation_contains","status":"public","id":"10799"}]},"main_file_link":[{"open_access":"1","url":"https://arxiv.org/abs/2102.05996"}],"abstract":[{"lang":"eng","text":"Given the abundance of applications of ranking in recent years, addressing fairness concerns around automated ranking systems becomes necessary for increasing the trust among end-users. Previous work on fair ranking has mostly focused on application-specific fairness notions, often tailored to online advertising, and it rarely considers learning as part of the process. In this work, we show how to transfer numerous fairness notions from binary classification to a learning to rank setting. Our formalism allows us to design methods for incorporating fairness objectives with provable generalization guarantees. An extensive experimental evaluation shows that our method can improve ranking fairness substantially with no or only little loss of model quality."}],"publication_status":"submitted","status":"public","language":[{"iso":"eng"}],"article_number":"2102.05996","oa":1,"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","type":"preprint","citation":{"ama":"Konstantinov NH, Lampert C. Fairness through regularization for learning to rank. <i>arXiv</i>. doi:<a href=\"https://doi.org/10.48550/arXiv.2102.05996\">10.48550/arXiv.2102.05996</a>","chicago":"Konstantinov, Nikola H, and Christoph Lampert. “Fairness through Regularization for Learning to Rank.” <i>ArXiv</i>, n.d. <a href=\"https://doi.org/10.48550/arXiv.2102.05996\">https://doi.org/10.48550/arXiv.2102.05996</a>.","mla":"Konstantinov, Nikola H., and Christoph Lampert. “Fairness through Regularization for Learning to Rank.” <i>ArXiv</i>, 2102.05996, doi:<a href=\"https://doi.org/10.48550/arXiv.2102.05996\">10.48550/arXiv.2102.05996</a>.","ista":"Konstantinov NH, Lampert C. Fairness through regularization for learning to rank. arXiv, 2102.05996.","short":"N.H. Konstantinov, C. Lampert, ArXiv (n.d.).","apa":"Konstantinov, N. H., &#38; Lampert, C. (n.d.). Fairness through regularization for learning to rank. <i>arXiv</i>. <a href=\"https://doi.org/10.48550/arXiv.2102.05996\">https://doi.org/10.48550/arXiv.2102.05996</a>","ieee":"N. H. Konstantinov and C. Lampert, “Fairness through regularization for learning to rank,” <i>arXiv</i>. ."},"department":[{"_id":"ChLa"}],"title":"Fairness through regularization for learning to rank","date_updated":"2023-09-07T13:42:08Z","month":"06","year":"2021","article_processing_charge":"No","date_published":"2021-06-07T00:00:00Z","author":[{"id":"4B9D76E4-F248-11E8-B48F-1D18A9856A87","first_name":"Nikola H","last_name":"Konstantinov","full_name":"Konstantinov, Nikola H"},{"orcid":"0000-0002-4561-241X","full_name":"Lampert, Christoph","last_name":"Lampert","first_name":"Christoph","id":"40C20FD2-F248-11E8-B48F-1D18A9856A87"}],"doi":"10.48550/arXiv.2102.05996","publication":"arXiv","arxiv":1,"oa_version":"Preprint","_id":"10803","day":"07","external_id":{"arxiv":["2102.05996"]},"date_created":"2022-02-28T14:13:59Z"}]