[{"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","article_processing_charge":"No","file_date_updated":"2023-05-05T09:06:00Z","language":[{"iso":"eng"}],"oa":1,"ddc":["000"],"year":"2022","publication_identifier":{"isbn":["978-3-200-08499-5"]},"tmp":{"short":"CC BY (4.0)","image":"/images/cc_by.png","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode"},"status":"public","oa_version":"Published Version","author":[{"first_name":"Alois","id":"45BF87EE-F248-11E8-B48F-1D18A9856A87","full_name":"Schlögl, Alois","last_name":"Schlögl","orcid":"0000-0002-5621-8100"},{"full_name":"Hornoiu, Andrei","last_name":"Hornoiu","first_name":"Andrei","id":"77129392-B450-11EA-8745-D4653DDC885E"},{"first_name":"Stefano","id":"490F40CE-F248-11E8-B48F-1D18A9856A87","full_name":"Elefante, Stefano","last_name":"Elefante"},{"full_name":"Stadlbauer, Stephan","last_name":"Stadlbauer","first_name":"Stephan","id":"4D0BC184-F248-11E8-B48F-1D18A9856A87"}],"page":"7","publisher":"EuroCC Austria c/o Universität Wien","publication_status":"published","type":"conference_abstract","has_accepted_license":"1","publication":"ASHPC22 - Austrian-Slovenian HPC Meeting 2022","day":"02","date_published":"2022-06-02T00:00:00Z","title":"Where is the sweet spot? A procurement story of general purpose compute nodes","conference":{"name":"ASHPC: Austrian-Slovenian HPC Meeting","end_date":"2022-06-02","location":"Grundlsee, Austria","start_date":"2022-05-31"},"_id":"12894","doi":"10.25365/phaidra.337","file":[{"creator":"schloegl","file_size":7180531,"file_name":"BOOKLET_ASHPC22.pdf","success":1,"checksum":"e3f8c240b85422ce2190e7b203cc2563","file_id":"12895","access_level":"open_access","relation":"main_file","date_created":"2023-05-05T09:06:00Z","date_updated":"2023-05-05T09:06:00Z","content_type":"application/pdf"}],"department":[{"_id":"ScienComp"}],"date_created":"2023-05-05T09:13:42Z","date_updated":"2023-05-16T07:42:56Z","citation":{"ama":"Schlögl A, Hornoiu A, Elefante S, Stadlbauer S. Where is the sweet spot? A procurement story of general purpose compute nodes. In: ASHPC22 - Austrian-Slovenian HPC Meeting 2022. EuroCC Austria c/o Universität Wien; 2022:7. doi:10.25365/phaidra.337","apa":"Schlögl, A., Hornoiu, A., Elefante, S., & Stadlbauer, S. (2022). Where is the sweet spot? A procurement story of general purpose compute nodes. In ASHPC22 - Austrian-Slovenian HPC Meeting 2022 (p. 7). Grundlsee, Austria: EuroCC Austria c/o Universität Wien. https://doi.org/10.25365/phaidra.337","ista":"Schlögl A, Hornoiu A, Elefante S, Stadlbauer S. 2022. Where is the sweet spot? A procurement story of general purpose compute nodes. ASHPC22 - Austrian-Slovenian HPC Meeting 2022. ASHPC: Austrian-Slovenian HPC Meeting, 7.","chicago":"Schlögl, Alois, Andrei Hornoiu, Stefano Elefante, and Stephan Stadlbauer. “Where Is the Sweet Spot? A Procurement Story of General Purpose Compute Nodes.” In ASHPC22 - Austrian-Slovenian HPC Meeting 2022, 7. EuroCC Austria c/o Universität Wien, 2022. https://doi.org/10.25365/phaidra.337.","mla":"Schlögl, Alois, et al. “Where Is the Sweet Spot? A Procurement Story of General Purpose Compute Nodes.” ASHPC22 - Austrian-Slovenian HPC Meeting 2022, EuroCC Austria c/o Universität Wien, 2022, p. 7, doi:10.25365/phaidra.337.","short":"A. Schlögl, A. Hornoiu, S. Elefante, S. Stadlbauer, in:, ASHPC22 - Austrian-Slovenian HPC Meeting 2022, EuroCC Austria c/o Universität Wien, 2022, p. 7.","ieee":"A. Schlögl, A. Hornoiu, S. Elefante, and S. Stadlbauer, “Where is the sweet spot? A procurement story of general purpose compute nodes,” in ASHPC22 - Austrian-Slovenian HPC Meeting 2022, Grundlsee, Austria, 2022, p. 7."},"acknowledgement":"The abstracts in this booklet are licenced under a CC BY 4.0 licence (https://creativecommons.org/licenses/by/4.0/legalcode), except Markus Wallerberger’s contribution at page 21, licenced under a CC BY-SA 4.0 licence (https://creativecommons.org/licenses/by-sa/4.0/legalcode).\r\n","month":"06"},{"abstract":[{"text":"Genetically informed, deep-phenotyped biobanks are an important research resource and it is imperative that the most powerful, versatile, and efficient analysis approaches are used. Here, we apply our recently developed Bayesian grouped mixture of regressions model (GMRM) in the UK and Estonian Biobanks and obtain the highest genomic prediction accuracy reported to date across 21 heritable traits. When compared to other approaches, GMRM accuracy was greater than annotation prediction models run in the LDAK or LDPred-funct software by 15% (SE 7%) and 14% (SE 2%), respectively, and was 18% (SE 3%) greater than a baseline BayesR model without single-nucleotide polymorphism (SNP) markers grouped into minor allele frequency–linkage disequilibrium (MAF-LD) annotation categories. For height, the prediction accuracy R 2 was 47% in a UK Biobank holdout sample, which was 76% of the estimated h SNP 2 . We then extend our GMRM prediction model to provide mixed-linear model association (MLMA) SNP marker estimates for genome-wide association (GWAS) discovery, which increased the independent loci detected to 16,162 in unrelated UK Biobank individuals, compared to 10,550 from BoltLMM and 10,095 from Regenie, a 62 and 65% increase, respectively. The average χ2 value of the leading markers increased by 15.24 (SE 0.41) for every 1% increase in prediction accuracy gained over a baseline BayesR model across the traits. Thus, we show that modeling genetic associations accounting for MAF and LD differences among SNP markers, and incorporating prior knowledge of genomic function, is important for both genomic prediction and discovery in large-scale individual-level studies.","lang":"eng"}],"article_processing_charge":"No","publisher":"Dryad","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","type":"research_data_reference","oa":1,"ddc":["570"],"title":"Improving genome-wide association discovery and genomic prediction accuracy in biobank data","date_published":"2022-09-02T00:00:00Z","day":"02","doi":"10.5061/DRYAD.GTHT76HMZ","main_file_link":[{"open_access":"1","url":"https://doi.org/10.5061/dryad.gtht76hmz"}],"tmp":{"image":"/images/cc_0.png","short":"CC0 (1.0)","legal_code_url":"https://creativecommons.org/publicdomain/zero/1.0/legalcode","name":"Creative Commons Public Domain Dedication (CC0 1.0)"},"_id":"13064","year":"2022","related_material":{"record":[{"id":"11733","relation":"used_in_publication","status":"public"}]},"citation":{"chicago":"Orliac, Etienne, Daniel Trejo Banos, Sven Ojavee, Kristi Läll, Reedik Mägi, Peter Visscher, and Matthew Richard Robinson. “Improving Genome-Wide Association Discovery and Genomic Prediction Accuracy in Biobank Data.” Dryad, 2022. https://doi.org/10.5061/DRYAD.GTHT76HMZ.","mla":"Orliac, Etienne, et al. Improving Genome-Wide Association Discovery and Genomic Prediction Accuracy in Biobank Data. Dryad, 2022, doi:10.5061/DRYAD.GTHT76HMZ.","short":"E. Orliac, D. Trejo Banos, S. Ojavee, K. Läll, R. Mägi, P. Visscher, M.R. Robinson, (2022).","ieee":"E. Orliac et al., “Improving genome-wide association discovery and genomic prediction accuracy in biobank data.” Dryad, 2022.","ama":"Orliac E, Trejo Banos D, Ojavee S, et al. Improving genome-wide association discovery and genomic prediction accuracy in biobank data. 2022. doi:10.5061/DRYAD.GTHT76HMZ","apa":"Orliac, E., Trejo Banos, D., Ojavee, S., Läll, K., Mägi, R., Visscher, P., & Robinson, M. R. (2022). Improving genome-wide association discovery and genomic prediction accuracy in biobank data. Dryad. https://doi.org/10.5061/DRYAD.GTHT76HMZ","ista":"Orliac E, Trejo Banos D, Ojavee S, Läll K, Mägi R, Visscher P, Robinson MR. 2022. Improving genome-wide association discovery and genomic prediction accuracy in biobank data, Dryad, 10.5061/DRYAD.GTHT76HMZ."},"month":"09","author":[{"first_name":"Etienne","full_name":"Orliac, Etienne","last_name":"Orliac"},{"first_name":"Daniel","last_name":"Trejo Banos","full_name":"Trejo Banos, Daniel"},{"last_name":"Ojavee","full_name":"Ojavee, Sven","first_name":"Sven"},{"last_name":"Läll","full_name":"Läll, Kristi","first_name":"Kristi"},{"first_name":"Reedik","full_name":"Mägi, Reedik","last_name":"Mägi"},{"full_name":"Visscher, Peter","last_name":"Visscher","first_name":"Peter"},{"id":"E5D42276-F5DA-11E9-8E24-6303E6697425","first_name":"Matthew Richard","orcid":"0000-0001-8982-8813","last_name":"Robinson","full_name":"Robinson, Matthew Richard"}],"status":"public","date_updated":"2023-08-03T12:40:37Z","date_created":"2023-05-23T16:28:13Z","oa_version":"Published Version","department":[{"_id":"MaRo"}]},{"year":"2022","_id":"13066","main_file_link":[{"url":"https://doi.org/10.5061/dryad.m905qfv4b","open_access":"1"}],"tmp":{"image":"/images/cc_0.png","short":"CC0 (1.0)","legal_code_url":"https://creativecommons.org/publicdomain/zero/1.0/legalcode","name":"Creative Commons Public Domain Dedication (CC0 1.0)"},"doi":"10.5061/DRYAD.M905QFV4B","date_updated":"2023-08-04T09:42:10Z","date_created":"2023-05-23T16:33:12Z","department":[{"_id":"NiBa"}],"oa_version":"Published Version","status":"public","month":"07","author":[{"first_name":"Eva","full_name":"Koch, Eva","last_name":"Koch"},{"first_name":"Mark","full_name":"Ravinet, Mark","last_name":"Ravinet"},{"id":"3C147470-F248-11E8-B48F-1D18A9856A87","first_name":"Anja M","orcid":"0000-0003-1050-4969","last_name":"Westram","full_name":"Westram, Anja M"},{"last_name":"Jonannesson","full_name":"Jonannesson, Kerstin","first_name":"Kerstin"},{"first_name":"Roger","last_name":"Butlin","full_name":"Butlin, Roger"}],"related_material":{"record":[{"relation":"used_in_publication","status":"public","id":"12247"}]},"citation":{"ama":"Koch E, Ravinet M, Westram AM, Jonannesson K, Butlin R. Data from: Genetic architecture of repeated phenotypic divergence in Littorina saxatilis ecotype evolution. 2022. doi:10.5061/DRYAD.M905QFV4B","apa":"Koch, E., Ravinet, M., Westram, A. M., Jonannesson, K., & Butlin, R. (2022). Data from: Genetic architecture of repeated phenotypic divergence in Littorina saxatilis ecotype evolution. Dryad. https://doi.org/10.5061/DRYAD.M905QFV4B","ista":"Koch E, Ravinet M, Westram AM, Jonannesson K, Butlin R. 2022. Data from: Genetic architecture of repeated phenotypic divergence in Littorina saxatilis ecotype evolution, Dryad, 10.5061/DRYAD.M905QFV4B.","chicago":"Koch, Eva, Mark Ravinet, Anja M Westram, Kerstin Jonannesson, and Roger Butlin. “Data from: Genetic Architecture of Repeated Phenotypic Divergence in Littorina Saxatilis Ecotype Evolution.” Dryad, 2022. https://doi.org/10.5061/DRYAD.M905QFV4B.","short":"E. Koch, M. Ravinet, A.M. Westram, K. Jonannesson, R. Butlin, (2022).","mla":"Koch, Eva, et al. Data from: Genetic Architecture of Repeated Phenotypic Divergence in Littorina Saxatilis Ecotype Evolution. Dryad, 2022, doi:10.5061/DRYAD.M905QFV4B.","ieee":"E. Koch, M. Ravinet, A. M. Westram, K. Jonannesson, and R. Butlin, “Data from: Genetic architecture of repeated phenotypic divergence in Littorina saxatilis ecotype evolution.” Dryad, 2022."},"type":"research_data_reference","abstract":[{"text":"Chromosomal inversions have been shown to play a major role in local adaptation by suppressing recombination between alternative arrangements and maintaining beneficial allele combinations. However, so far, their importance relative to the remaining genome remains largely unknown. Understanding the genetic architecture of adaptation requires better estimates of how loci of different effect sizes contribute to phenotypic variation. Here, we used three Swedish islands where the marine snail Littorina saxatilis has repeatedly evolved into two distinct ecotypes along a habitat transition. We estimated the contribution of inversion polymorphisms to phenotypic divergence while controlling for polygenic effects in the remaining genome using a quantitative genetics framework. We confirmed the importance of inversions but showed that contributions of loci outside inversions are of similar magnitude, with variable proportions dependent on the trait and the population. Some inversions showed consistent effects across all sites, whereas others exhibited site-specific effects, indicating that the genomic basis for replicated phenotypic divergence is only partly shared. The contributions of sexual dimorphism as well as environmental factors to phenotypic variation were significant but minor compared to inversions and polygenic background. Overall, this integrated approach provides insight into the multiple mechanisms contributing to parallel phenotypic divergence.","lang":"eng"}],"article_processing_charge":"No","publisher":"Dryad","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","title":"Data from: Genetic architecture of repeated phenotypic divergence in Littorina saxatilis ecotype evolution","date_published":"2022-07-28T00:00:00Z","day":"28","ddc":["570"],"oa":1},{"article_processing_charge":"No","abstract":[{"lang":"eng","text":"The source code for replicating experiments presented in the paper.\r\n\r\nThe implementation of the designed priority schedulers can be found in Galois-2.2.1/include/Galois/WorkList/:\r\nStealingMultiQueue.h is the StealingMultiQueue.\r\nMQOptimized/ contains MQ Optimized variants.\r\n\r\nWe provide images that contain all the dependencies and datasets. Images can be pulled from npostnikova/mq-based-schedulers repository, or downloaded from Zenodo. See readme for more detail."}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","publisher":"Zenodo","type":"research_data_reference","date_published":"2022-01-03T00:00:00Z","title":"Multi-queues can be state-of-the-art priority schedulers","day":"03","oa":1,"ddc":["510"],"_id":"13076","year":"2022","doi":"10.5281/ZENODO.5733408","main_file_link":[{"open_access":"1","url":"https://doi.org/10.5281/zenodo.5813846"}],"status":"public","date_created":"2023-05-23T17:05:40Z","date_updated":"2023-08-03T06:48:34Z","department":[{"_id":"DaAl"}],"oa_version":"Published Version","related_material":{"link":[{"url":"https://github.com/npostnikova/mq-based-schedulers/tree/v1.1","relation":"software"}],"record":[{"relation":"used_in_publication","status":"public","id":"11180"}]},"citation":{"ista":"Postnikova A, Koval N, Nadiradze G, Alistarh D-A. 2022. Multi-queues can be state-of-the-art priority schedulers, Zenodo, 10.5281/ZENODO.5733408.","ama":"Postnikova A, Koval N, Nadiradze G, Alistarh D-A. Multi-queues can be state-of-the-art priority schedulers. 2022. doi:10.5281/ZENODO.5733408","apa":"Postnikova, A., Koval, N., Nadiradze, G., & Alistarh, D.-A. (2022). Multi-queues can be state-of-the-art priority schedulers. Zenodo. https://doi.org/10.5281/ZENODO.5733408","mla":"Postnikova, Anastasiia, et al. Multi-Queues Can Be State-of-the-Art Priority Schedulers. Zenodo, 2022, doi:10.5281/ZENODO.5733408.","short":"A. Postnikova, N. Koval, G. Nadiradze, D.-A. Alistarh, (2022).","ieee":"A. Postnikova, N. Koval, G. Nadiradze, and D.-A. Alistarh, “Multi-queues can be state-of-the-art priority schedulers.” Zenodo, 2022.","chicago":"Postnikova, Anastasiia, Nikita Koval, Giorgi Nadiradze, and Dan-Adrian Alistarh. “Multi-Queues Can Be State-of-the-Art Priority Schedulers.” Zenodo, 2022. https://doi.org/10.5281/ZENODO.5733408."},"month":"01","author":[{"first_name":"Anastasiia","last_name":"Postnikova","full_name":"Postnikova, Anastasiia"},{"full_name":"Koval, Nikita","last_name":"Koval","first_name":"Nikita","id":"2F4DB10C-F248-11E8-B48F-1D18A9856A87"},{"full_name":"Nadiradze, Giorgi","last_name":"Nadiradze","id":"3279A00C-F248-11E8-B48F-1D18A9856A87","first_name":"Giorgi"},{"id":"4A899BFC-F248-11E8-B48F-1D18A9856A87","first_name":"Dan-Adrian","orcid":"0000-0003-3650-940X","full_name":"Alistarh, Dan-Adrian","last_name":"Alistarh"}]},{"publication_identifier":{"eissn":["2640-3498"]},"ec_funded":1,"year":"2022","author":[{"full_name":"Van Der Plas, Thijs L.","last_name":"Van Der Plas","first_name":"Thijs L."},{"orcid":"0000-0003-3295-6181","full_name":"Vogels, Tim P","last_name":"Vogels","first_name":"Tim P","id":"CB6FF8D2-008F-11EA-8E08-2637E6697425"},{"first_name":"Sanjay G.","full_name":"Manohar, Sanjay G.","last_name":"Manohar"}],"page":"518-531","status":"public","oa_version":"Published Version","file_date_updated":"2023-07-18T06:32:38Z","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","abstract":[{"lang":"eng","text":"Brains are thought to engage in predictive learning - learning to predict upcoming stimuli - to construct an internal model of their environment. This is especially notable for spatial navigation, as first described by Tolman’s latent learning tasks. However, predictive learning has also been observed in sensory cortex, in settings unrelated to spatial navigation. Apart from normative frameworks such as active inference or efficient coding, what could be the utility of learning to predict the patterns of occurrence of correlated stimuli? Here we show that prediction, and thereby the construction of an internal model of sequential stimuli, can bootstrap the learning process of a working memory task in a recurrent neural network. We implemented predictive learning alongside working memory match-tasks, and networks emerged to solve the prediction task first by encoding information across time to predict upcoming stimuli, and then eavesdropped on this solution to solve the matching task. Eavesdropping was most beneficial when neural resources were limited. Hence, predictive learning acts as a general neural mechanism to learn to store sensory information that can later be essential for working memory tasks."}],"article_processing_charge":"No","oa":1,"ddc":["000"],"language":[{"iso":"eng"}],"project":[{"name":"Learning the shape of synaptic plasticity rules for neuronal architectures and function through machine learning.","grant_number":"819603","call_identifier":"H2020","_id":"0aacfa84-070f-11eb-9043-d7eb2c709234"}],"file":[{"success":1,"file_id":"13243","checksum":"7530a93ef42e10b4db1e5e4b69796e93","date_created":"2023-07-18T06:32:38Z","access_level":"open_access","date_updated":"2023-07-18T06:32:38Z","relation":"main_file","content_type":"application/pdf","creator":"dernst","file_size":585135,"file_name":"2022_PMLR_vanderPlas.pdf"}],"volume":199,"_id":"13239","citation":{"ista":"Van Der Plas TL, Vogels TP, Manohar SG. 2022. Predictive learning enables neural networks to learn complex working memory tasks. Proceedings of Machine Learning Research. vol. 199, 518–531.","ama":"Van Der Plas TL, Vogels TP, Manohar SG. Predictive learning enables neural networks to learn complex working memory tasks. In: Proceedings of Machine Learning Research. Vol 199. ML Research Press; 2022:518-531.","apa":"Van Der Plas, T. L., Vogels, T. P., & Manohar, S. G. (2022). Predictive learning enables neural networks to learn complex working memory tasks. In Proceedings of Machine Learning Research (Vol. 199, pp. 518–531). ML Research Press.","short":"T.L. Van Der Plas, T.P. Vogels, S.G. Manohar, in:, Proceedings of Machine Learning Research, ML Research Press, 2022, pp. 518–531.","mla":"Van Der Plas, Thijs L., et al. “Predictive Learning Enables Neural Networks to Learn Complex Working Memory Tasks.” Proceedings of Machine Learning Research, vol. 199, ML Research Press, 2022, pp. 518–31.","ieee":"T. L. Van Der Plas, T. P. Vogels, and S. G. Manohar, “Predictive learning enables neural networks to learn complex working memory tasks,” in Proceedings of Machine Learning Research, 2022, vol. 199, pp. 518–531.","chicago":"Van Der Plas, Thijs L., Tim P Vogels, and Sanjay G. Manohar. “Predictive Learning Enables Neural Networks to Learn Complex Working Memory Tasks.” In Proceedings of Machine Learning Research, 199:518–31. ML Research Press, 2022."},"acknowledgement":"The authors would like to thank members of the Vogels lab and Manohar lab, as well as Adam Packer, Andrew Saxe, Stefano Sarao Mannelli and Jacob Bakermans for fruitful discussions and comments on earlier versions of the manuscript.\r\nTLvdP was supported by funding from the Biotechnology and Biological Sciences Research Council (BBSRC) [grant number BB/M011224/1]. TPV was supported by an ERC Consolidator Grant (SYNAPSEEK). SGM was funded by a MRC Clinician Scientist Fellowship MR/P00878X and Leverhulme Grant RPG-2018-310.","month":"12","intvolume":" 199","department":[{"_id":"TiVo"}],"date_created":"2023-07-16T22:01:12Z","date_updated":"2023-07-18T06:36:28Z","has_accepted_license":"1","publisher":"ML Research Press","quality_controlled":"1","publication_status":"published","type":"conference","scopus_import":"1","publication":"Proceedings of Machine Learning Research","day":"01","date_published":"2022-12-01T00:00:00Z","title":"Predictive learning enables neural networks to learn complex working memory tasks"},{"_id":"13240","volume":3,"file":[{"file_size":27966699,"file_name":"2023_FrontiersFungalBio_Ingole.pdf","creator":"dernst","content_type":"application/pdf","success":1,"date_created":"2023-07-17T11:46:34Z","date_updated":"2023-07-17T11:46:34Z","relation":"main_file","access_level":"open_access","checksum":"2254e0119c0749d6f7237084fefcece6","file_id":"13242"}],"doi":"10.3389/ffunb.2022.1029114","date_updated":"2024-03-06T14:01:57Z","date_created":"2023-07-16T22:01:12Z","department":[{"_id":"JiFr"}],"intvolume":" 3","month":"10","article_type":"original","acknowledgement":"The research leading to these results received funding from the European Research Council under the European Union’s Seventh Framework Programme ERC-2013-STG (grant agreement: 335691), the Austrian Science Fund (I 3033-B22), the Austrian Academy of Sciences, and the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany's Excellence Strategy EXC-2070-390732324 (PhenoRob) and DFG grant (DJ 64/5-1).\r\nWe would like to thank the GMI/IMBA/IMP core facilities for their excellent technical support. We would like to acknowledge Dr. Sinéad A. O’Sullivan from DZNE, University of Bonn for providing anti-GFP antibodies. The authors are thankful to the Excellence University of Bonn for providing infrastructure and instrumentation facilities at the INRES-Plant Pathology department.","citation":{"ieee":"K. D. Ingole, N. Nagarajan, S. Uhse, C. Giannini, and A. Djamei, “Tetracycline-controlled (TetON) gene expression system for the smut fungus Ustilago maydis,” Frontiers in Fungal Biology, vol. 3. Frontiers Media, 2022.","short":"K.D. Ingole, N. Nagarajan, S. Uhse, C. Giannini, A. Djamei, Frontiers in Fungal Biology 3 (2022).","mla":"Ingole, Kishor D., et al. “Tetracycline-Controlled (TetON) Gene Expression System for the Smut Fungus Ustilago Maydis.” Frontiers in Fungal Biology, vol. 3, 1029114, Frontiers Media, 2022, doi:10.3389/ffunb.2022.1029114.","chicago":"Ingole, Kishor D., Nithya Nagarajan, Simon Uhse, Caterina Giannini, and Armin Djamei. “Tetracycline-Controlled (TetON) Gene Expression System for the Smut Fungus Ustilago Maydis.” Frontiers in Fungal Biology. Frontiers Media, 2022. https://doi.org/10.3389/ffunb.2022.1029114.","ista":"Ingole KD, Nagarajan N, Uhse S, Giannini C, Djamei A. 2022. Tetracycline-controlled (TetON) gene expression system for the smut fungus Ustilago maydis. Frontiers in Fungal Biology. 3, 1029114.","apa":"Ingole, K. D., Nagarajan, N., Uhse, S., Giannini, C., & Djamei, A. (2022). Tetracycline-controlled (TetON) gene expression system for the smut fungus Ustilago maydis. Frontiers in Fungal Biology. Frontiers Media. https://doi.org/10.3389/ffunb.2022.1029114","ama":"Ingole KD, Nagarajan N, Uhse S, Giannini C, Djamei A. Tetracycline-controlled (TetON) gene expression system for the smut fungus Ustilago maydis. Frontiers in Fungal Biology. 2022;3. doi:10.3389/ffunb.2022.1029114"},"publication_status":"published","scopus_import":"1","quality_controlled":"1","type":"journal_article","publisher":"Frontiers Media","has_accepted_license":"1","date_published":"2022-10-19T00:00:00Z","title":"Tetracycline-controlled (TetON) gene expression system for the smut fungus Ustilago maydis","day":"19","publication":"Frontiers in Fungal Biology","year":"2022","tmp":{"short":"CC BY (4.0)","image":"/images/cc_by.png","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":["2673-6128"]},"oa_version":"Published Version","status":"public","author":[{"last_name":"Ingole","full_name":"Ingole, Kishor D.","first_name":"Kishor D."},{"first_name":"Nithya","last_name":"Nagarajan","full_name":"Nagarajan, Nithya"},{"last_name":"Uhse","full_name":"Uhse, Simon","first_name":"Simon"},{"full_name":"Giannini, Caterina","last_name":"Giannini","id":"e3fdddd5-f6e0-11ea-865d-ca99ee6367f4","first_name":"Caterina"},{"full_name":"Djamei, Armin","last_name":"Djamei","first_name":"Armin"}],"abstract":[{"text":"Ustilago maydis is a biotrophic phytopathogenic fungus that causes corn smut disease. As a well-established model system, U. maydis is genetically fully accessible with large omics datasets available and subject to various biological questions ranging from DNA-repair, RNA-transport, and protein secretion to disease biology. For many genetic approaches, tight control of transgene regulation is important. Here we established an optimised version of the Tetracycline-ON (TetON) system for U. maydis. We demonstrate the Tetracycline concentration-dependent expression of fluorescent protein transgenes and the system’s suitability for the induced expression of the toxic protein BCL2 Associated X-1 (Bax1). The Golden Gate compatible vector system contains a native minimal promoter from the mating factor a-1 encoding gene, mfa with ten copies of the tet-regulated operator (tetO) and a codon optimised Tet-repressor (tetR*) which is translationally fused to the native transcriptional corepressor Mql1 (UMAG_05501). The metabolism-independent transcriptional regulator system is functional both, in liquid culture as well as on solid media in the presence of the inducer and can become a useful tool for toxin-antitoxin studies, identification of antifungal proteins, and to study functions of toxic gene products in Ustilago maydis.","lang":"eng"}],"article_processing_charge":"Yes","user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87","article_number":"1029114","file_date_updated":"2023-07-17T11:46:34Z","language":[{"iso":"eng"}],"ddc":["579"],"oa":1},{"publication_identifier":{"eissn":["2640-3498"]},"year":"2022","related_material":{"record":[{"relation":"extended_version","status":"public","id":"10802"}]},"page":"59-83","author":[{"first_name":"Nikola H","id":"4B9D76E4-F248-11E8-B48F-1D18A9856A87","full_name":"Konstantinov, Nikola H","last_name":"Konstantinov"},{"full_name":"Lampert, Christoph","last_name":"Lampert","orcid":"0000-0001-8622-7887","first_name":"Christoph","id":"40C20FD2-F248-11E8-B48F-1D18A9856A87"}],"status":"public","oa_version":"Preprint","abstract":[{"text":"Addressing fairness concerns about machine learning models is a crucial step towards their long-term adoption in real-world automated systems. Many approaches for training fair models from data have been developed and an implicit assumption about such algorithms is that they are able to recover a fair model, despite potential historical biases in the data. In this work we show a number of impossibility results that indicate that there is no learning algorithm that can recover a fair model when a proportion of the dataset is subject to arbitrary manipulations. Specifically, we prove that there are situations in which an adversary can force any learner to return a biased classifier, with or without degrading accuracy, and that the strength of this bias increases for learning problems with underrepresented protected groups in the data. Our results emphasize on the importance of studying further data corruption models of various strength and of establishing stricter data collection practices for fairness-aware learning.","lang":"eng"}],"article_processing_charge":"No","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","external_id":{"arxiv":["2102.06004"]},"oa":1,"language":[{"iso":"eng"}],"main_file_link":[{"open_access":"1","url":"https://arxiv.org/abs/2102.06004"}],"volume":171,"_id":"13241","acknowledgement":"This paper is a shortened, workshop version of Konstantinov and Lampert (2021),\r\nhttps://arxiv.org/abs/2102.06004. For further results, including an analysis of algorithms achieving the lower bounds from this paper, we refer to the full version.","citation":{"ama":"Konstantinov NH, Lampert C. On the impossibility of fairness-aware learning from corrupted data. In: Proceedings of Machine Learning Research. Vol 171. ML Research Press; 2022:59-83.","apa":"Konstantinov, N. H., & Lampert, C. (2022). On the impossibility of fairness-aware learning from corrupted data. In Proceedings of Machine Learning Research (Vol. 171, pp. 59–83). ML Research Press.","ista":"Konstantinov NH, Lampert C. 2022. On the impossibility of fairness-aware learning from corrupted data. Proceedings of Machine Learning Research. vol. 171, 59–83.","chicago":"Konstantinov, Nikola H, and Christoph Lampert. “On the Impossibility of Fairness-Aware Learning from Corrupted Data.” In Proceedings of Machine Learning Research, 171:59–83. ML Research Press, 2022.","short":"N.H. Konstantinov, C. Lampert, in:, Proceedings of Machine Learning Research, ML Research Press, 2022, pp. 59–83.","mla":"Konstantinov, Nikola H., and Christoph Lampert. “On the Impossibility of Fairness-Aware Learning from Corrupted Data.” Proceedings of Machine Learning Research, vol. 171, ML Research Press, 2022, pp. 59–83.","ieee":"N. H. Konstantinov and C. Lampert, “On the impossibility of fairness-aware learning from corrupted data,” in Proceedings of Machine Learning Research, 2022, vol. 171, pp. 59–83."},"month":"12","intvolume":" 171","date_updated":"2023-09-26T10:44:37Z","date_created":"2023-07-16T22:01:13Z","department":[{"_id":"ChLa"}],"arxiv":1,"publisher":"ML Research Press","quality_controlled":"1","scopus_import":"1","publication_status":"published","type":"conference","publication":"Proceedings of Machine Learning Research","date_published":"2022-12-01T00:00:00Z","title":"On the impossibility of fairness-aware learning from corrupted data","day":"01"},{"day":"01","date_published":"2022-12-01T00:00:00Z","title":"Equidistribution and freeness on Grassmannians","publication":"Algebra & Number Theory","isi":1,"type":"journal_article","publication_status":"published","scopus_import":"1","quality_controlled":"1","publisher":"Mathematical Sciences Publishers","arxiv":1,"department":[{"_id":"TiBr"}],"date_created":"2021-02-25T09:56:57Z","date_updated":"2023-08-02T06:46:38Z","intvolume":" 16","month":"12","article_type":"original","citation":{"chicago":"Browning, Timothy D, Tal Horesh, and Florian Alexander Wilsch. “Equidistribution and Freeness on Grassmannians.” Algebra & Number Theory. Mathematical Sciences Publishers, 2022. https://doi.org/10.2140/ant.2022.16.2385.","ieee":"T. D. Browning, T. Horesh, and F. A. Wilsch, “Equidistribution and freeness on Grassmannians,” Algebra & Number Theory, vol. 16, no. 10. Mathematical Sciences Publishers, pp. 2385–2407, 2022.","short":"T.D. Browning, T. Horesh, F.A. Wilsch, Algebra & Number Theory 16 (2022) 2385–2407.","mla":"Browning, Timothy D., et al. “Equidistribution and Freeness on Grassmannians.” Algebra & Number Theory, vol. 16, no. 10, Mathematical Sciences Publishers, 2022, pp. 2385–407, doi:10.2140/ant.2022.16.2385.","apa":"Browning, T. D., Horesh, T., & Wilsch, F. A. (2022). Equidistribution and freeness on Grassmannians. Algebra & Number Theory. Mathematical Sciences Publishers. https://doi.org/10.2140/ant.2022.16.2385","ama":"Browning TD, Horesh T, Wilsch FA. Equidistribution and freeness on Grassmannians. Algebra & Number Theory. 2022;16(10):2385-2407. doi:10.2140/ant.2022.16.2385","ista":"Browning TD, Horesh T, Wilsch FA. 2022. Equidistribution and freeness on Grassmannians. Algebra & Number Theory. 16(10), 2385–2407."},"acknowledgement":"The authors are very grateful to Will Sawin for useful remarks about this topic. While working on this paper the first two authors were supported by EPSRC grant EP/P026710/1, and the first and last authors by FWF grant P 32428-N35.","issue":"10","_id":"9199","main_file_link":[{"open_access":"1","url":"https://arxiv.org/abs/2102.11552"}],"volume":16,"doi":"10.2140/ant.2022.16.2385","project":[{"name":"Between rational and integral points","grant_number":"EP-P026710-2","_id":"26A8D266-B435-11E9-9278-68D0E5697425"},{"call_identifier":"FWF","grant_number":"P32428","name":"New frontiers of the Manin conjecture","_id":"26AEDAB2-B435-11E9-9278-68D0E5697425"}],"language":[{"iso":"eng"}],"oa":1,"external_id":{"isi":["000961514100004"],"arxiv":["2102.11552"]},"user_id":"4359f0d1-fa6c-11eb-b949-802e58b17ae8","abstract":[{"lang":"eng","text":"We associate a certain tensor product lattice to any primitive integer lattice and ask about its typical shape. These lattices are related to the tangent bundle of Grassmannians and their study is motivated by Peyre's programme on \"freeness\" for rational points of bounded height on Fano\r\nvarieties."}],"article_processing_charge":"No","oa_version":"Preprint","status":"public","author":[{"last_name":"Browning","full_name":"Browning, Timothy D","orcid":"0000-0002-8314-0177","first_name":"Timothy D","id":"35827D50-F248-11E8-B48F-1D18A9856A87"},{"last_name":"Horesh","full_name":"Horesh, Tal","id":"C8B7BF48-8D81-11E9-BCA9-F536E6697425","first_name":"Tal"},{"orcid":"0000-0001-7302-8256","last_name":"Wilsch","full_name":"Wilsch, Florian Alexander","id":"560601DA-8D36-11E9-A136-7AC1E5697425","first_name":"Florian Alexander"}],"page":"2385-2407","year":"2022","publication_identifier":{"eissn":["1944-7833"],"issn":["1937-0652"]}},{"year":"2022","publication_identifier":{"eissn":["1526-5471"],"issn":["0364-765X"]},"oa_version":"Preprint","status":"public","author":[{"first_name":"Krishnendu","id":"2E5DCA20-F248-11E8-B48F-1D18A9856A87","full_name":"Chatterjee, Krishnendu","last_name":"Chatterjee","orcid":"0000-0002-4561-241X"},{"first_name":"Raimundo J","id":"BD1DF4C4-D767-11E9-B658-BC13E6697425","full_name":"Saona Urmeneta, Raimundo J","last_name":"Saona Urmeneta","orcid":"0000-0001-5103-038X"},{"full_name":"Ziliotto, Bruno","last_name":"Ziliotto","first_name":"Bruno"}],"page":"100-119","external_id":{"arxiv":["1904.13360"],"isi":["000731918100001"]},"user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","abstract":[{"lang":"eng","text":"Partially observable Markov decision processes (POMDPs) are standard models for dynamic systems with probabilistic and nondeterministic behaviour in uncertain environments. We prove that in POMDPs with long-run average objective, the decision maker has approximately optimal strategies with finite memory. This implies notably that approximating the long-run value is recursively enumerable, as well as a weak continuity property of the value with respect to the transition function. "}],"article_processing_charge":"No","language":[{"iso":"eng"}],"oa":1,"issue":"1","_id":"9311","main_file_link":[{"url":"https://arxiv.org/abs/1904.13360","open_access":"1"}],"volume":47,"doi":"10.1287/moor.2020.1116","project":[{"call_identifier":"FWF","grant_number":"S11407","name":"Game Theory","_id":"25863FF4-B435-11E9-9278-68D0E5697425"}],"department":[{"_id":"GradSch"},{"_id":"KrCh"}],"date_created":"2021-04-08T09:33:31Z","date_updated":"2023-09-05T13:16:11Z","intvolume":" 47","article_type":"original","month":"02","citation":{"ista":"Chatterjee K, Saona Urmeneta RJ, Ziliotto B. 2022. Finite-memory strategies in POMDPs with long-run average objectives. Mathematics of Operations Research. 47(1), 100–119.","apa":"Chatterjee, K., Saona Urmeneta, R. J., & Ziliotto, B. (2022). Finite-memory strategies in POMDPs with long-run average objectives. Mathematics of Operations Research. Institute for Operations Research and the Management Sciences. https://doi.org/10.1287/moor.2020.1116","ama":"Chatterjee K, Saona Urmeneta RJ, Ziliotto B. Finite-memory strategies in POMDPs with long-run average objectives. Mathematics of Operations Research. 2022;47(1):100-119. doi:10.1287/moor.2020.1116","ieee":"K. Chatterjee, R. J. Saona Urmeneta, and B. Ziliotto, “Finite-memory strategies in POMDPs with long-run average objectives,” Mathematics of Operations Research, vol. 47, no. 1. Institute for Operations Research and the Management Sciences, pp. 100–119, 2022.","mla":"Chatterjee, Krishnendu, et al. “Finite-Memory Strategies in POMDPs with Long-Run Average Objectives.” Mathematics of Operations Research, vol. 47, no. 1, Institute for Operations Research and the Management Sciences, 2022, pp. 100–19, doi:10.1287/moor.2020.1116.","short":"K. Chatterjee, R.J. Saona Urmeneta, B. Ziliotto, Mathematics of Operations Research 47 (2022) 100–119.","chicago":"Chatterjee, Krishnendu, Raimundo J Saona Urmeneta, and Bruno Ziliotto. “Finite-Memory Strategies in POMDPs with Long-Run Average Objectives.” Mathematics of Operations Research. Institute for Operations Research and the Management Sciences, 2022. https://doi.org/10.1287/moor.2020.1116."},"acknowledgement":"Partially supported by Austrian Science Fund (FWF) NFN Grant No RiSE/SHiNE S11407, by CONICYT Chile through grant PII 20150140, and by ECOS-CONICYT through grant C15E03.\r\n","publication_status":"published","scopus_import":"1","type":"journal_article","quality_controlled":"1","publisher":"Institute for Operations Research and the Management Sciences","arxiv":1,"day":"01","keyword":["Management Science and Operations Research","General Mathematics","Computer Science Applications"],"date_published":"2022-02-01T00:00:00Z","title":"Finite-memory strategies in POMDPs with long-run average objectives","publication":"Mathematics of Operations Research","isi":1},{"publisher":"Cambridge University Press","quality_controlled":"1","publication_status":"published","type":"journal_article","scopus_import":"1","arxiv":1,"has_accepted_license":"1","publication":"Mathematical Proceedings of the Cambridge Philosophical Society","isi":1,"day":"01","title":"On the size of the maximum of incomplete Kloosterman sums","date_published":"2022-05-01T00:00:00Z","_id":"9364","issue":"3","doi":"10.1017/S030500412100030X","file":[{"creator":"cchlebak","file_size":334064,"file_name":"2021_MathProcCamPhilSoc_Bonolis.pdf","file_id":"10395","checksum":"614d2e9b83a78100408e4ee7752a80a8","access_level":"open_access","relation":"main_file","date_updated":"2021-12-01T14:01:54Z","date_created":"2021-12-01T14:01:54Z","success":1,"content_type":"application/pdf"}],"volume":172,"intvolume":" 172","department":[{"_id":"TiBr"}],"date_updated":"2023-08-02T06:47:48Z","date_created":"2021-05-02T22:01:29Z","citation":{"ama":"Bonolis D. On the size of the maximum of incomplete Kloosterman sums. Mathematical Proceedings of the Cambridge Philosophical Society. 2022;172(3):563-590. doi:10.1017/S030500412100030X","apa":"Bonolis, D. (2022). On the size of the maximum of incomplete Kloosterman sums. Mathematical Proceedings of the Cambridge Philosophical Society. Cambridge University Press. https://doi.org/10.1017/S030500412100030X","ista":"Bonolis D. 2022. On the size of the maximum of incomplete Kloosterman sums. Mathematical Proceedings of the Cambridge Philosophical Society. 172(3), 563–590.","chicago":"Bonolis, Dante. “On the Size of the Maximum of Incomplete Kloosterman Sums.” Mathematical Proceedings of the Cambridge Philosophical Society. Cambridge University Press, 2022. https://doi.org/10.1017/S030500412100030X.","short":"D. Bonolis, Mathematical Proceedings of the Cambridge Philosophical Society 172 (2022) 563–590.","mla":"Bonolis, Dante. “On the Size of the Maximum of Incomplete Kloosterman Sums.” Mathematical Proceedings of the Cambridge Philosophical Society, vol. 172, no. 3, Cambridge University Press, 2022, pp. 563–90, doi:10.1017/S030500412100030X.","ieee":"D. Bonolis, “On the size of the maximum of incomplete Kloosterman sums,” Mathematical Proceedings of the Cambridge Philosophical Society, vol. 172, no. 3. Cambridge University Press, pp. 563–590, 2022."},"acknowledgement":"I am most thankful to my advisor, Emmanuel Kowalski, for suggesting this problem and for his guidance during these years. I also would like to thank Youness Lamzouri for informing me about his work on sum of incomplete Birch sums and Tal Horesh for her suggestions on a previous version of the paper. Finally, I am very grateful to the anonymous referee for their careful reading of the manuscript and their valuable comments.","month":"05","article_type":"original","user_id":"4359f0d1-fa6c-11eb-b949-802e58b17ae8","article_processing_charge":"Yes (via OA deal)","abstract":[{"lang":"eng","text":"Let t : Fp → C be a complex valued function on Fp. A classical problem in analytic number theory is bounding the maximum M(t) := max 0≤H 0 there exists a large subset of a ∈ F×p such that for kl a,1,p : x → e((ax+x) / p) we have M(kla,1,p) ≥ (1−ε/√2π + o(1)) log log p, as p→∞. Finally, we prove a result on the growth of the moments of {M (kla,1,p)}a∈F×p. 2020 Mathematics Subject Classification: 11L03, 11T23 (Primary); 14F20, 60F10 (Secondary)."}],"external_id":{"arxiv":["1811.10563"],"isi":["000784421500001"]},"file_date_updated":"2021-12-01T14:01:54Z","language":[{"iso":"eng"}],"oa":1,"ddc":["510"],"year":"2022","publication_identifier":{"eissn":["1469-8064"],"issn":["0305-0041"]},"tmp":{"short":"CC BY (4.0)","image":"/images/cc_by.png","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode"},"status":"public","oa_version":"Published Version","author":[{"full_name":"Bonolis, Dante","last_name":"Bonolis","first_name":"Dante","id":"6A459894-5FDD-11E9-AF35-BB24E6697425"}],"page":"563 - 590"},{"article_processing_charge":"No","abstract":[{"lang":"eng","text":"Weak convergence of inertial iterative method for solving variational inequalities is the focus of this paper. The cost function is assumed to be non-Lipschitz and monotone. We propose a projection-type method with inertial terms and give weak convergence analysis under appropriate conditions. Some test results are performed and compared with relevant methods in the literature to show the efficiency and advantages given by our proposed methods."}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","external_id":{"isi":["000518364100001"],"arxiv":["2101.08057"]},"file_date_updated":"2021-03-16T23:30:06Z","language":[{"iso":"eng"}],"oa":1,"ddc":["510","515","518"],"year":"2022","publication_identifier":{"issn":["0003-6811"],"eissn":["1563-504X"]},"ec_funded":1,"status":"public","oa_version":"Submitted Version","page":"192-216","author":[{"full_name":"Shehu, Yekini","last_name":"Shehu","orcid":"0000-0001-9224-7139","first_name":"Yekini","id":"3FC7CB58-F248-11E8-B48F-1D18A9856A87"},{"full_name":"Iyiola, Olaniyi S.","last_name":"Iyiola","first_name":"Olaniyi S."}],"publisher":"Taylor & Francis","type":"journal_article","scopus_import":"1","quality_controlled":"1","publication_status":"published","has_accepted_license":"1","arxiv":1,"isi":1,"publication":"Applicable Analysis","date_published":"2022-01-01T00:00:00Z","title":"Weak convergence for variational inequalities with inertial-type method","day":"01","_id":"7577","issue":"1","project":[{"call_identifier":"FP7","name":"Discrete Optimization in Computer Vision: Theory and Practice","grant_number":"616160","_id":"25FBA906-B435-11E9-9278-68D0E5697425"}],"doi":"10.1080/00036811.2020.1736287","volume":101,"file":[{"date_created":"2020-10-12T10:42:54Z","access_level":"open_access","relation":"main_file","date_updated":"2021-03-16T23:30:06Z","file_id":"8648","checksum":"869efe8cb09505dfa6012f67d20db63d","content_type":"application/pdf","embargo":"2021-03-15","creator":"dernst","file_name":"2020_ApplicAnalysis_Shehu.pdf","file_size":4282586}],"intvolume":" 101","date_updated":"2024-03-05T14:01:52Z","date_created":"2020-03-09T07:06:52Z","department":[{"_id":"VlKo"}],"acknowledgement":"The project of the first author has received funding from the European Research Council (ERC) under the European Union's Seventh Framework Program (FP7 - 2007-2013) (Grant agreement No. 616160).","citation":{"chicago":"Shehu, Yekini, and Olaniyi S. Iyiola. “Weak Convergence for Variational Inequalities with Inertial-Type Method.” Applicable Analysis. Taylor & Francis, 2022. https://doi.org/10.1080/00036811.2020.1736287.","ieee":"Y. Shehu and O. S. Iyiola, “Weak convergence for variational inequalities with inertial-type method,” Applicable Analysis, vol. 101, no. 1. Taylor & Francis, pp. 192–216, 2022.","mla":"Shehu, Yekini, and Olaniyi S. Iyiola. “Weak Convergence for Variational Inequalities with Inertial-Type Method.” Applicable Analysis, vol. 101, no. 1, Taylor & Francis, 2022, pp. 192–216, doi:10.1080/00036811.2020.1736287.","short":"Y. Shehu, O.S. Iyiola, Applicable Analysis 101 (2022) 192–216.","apa":"Shehu, Y., & Iyiola, O. S. (2022). Weak convergence for variational inequalities with inertial-type method. Applicable Analysis. Taylor & Francis. https://doi.org/10.1080/00036811.2020.1736287","ama":"Shehu Y, Iyiola OS. Weak convergence for variational inequalities with inertial-type method. Applicable Analysis. 2022;101(1):192-216. doi:10.1080/00036811.2020.1736287","ista":"Shehu Y, Iyiola OS. 2022. Weak convergence for variational inequalities with inertial-type method. Applicable Analysis. 101(1), 192–216."},"month":"01","article_type":"original"},{"date_updated":"2024-02-22T15:58:42Z","date_created":"2020-05-03T22:00:48Z","department":[{"_id":"HeEd"}],"intvolume":" 8","article_type":"original","month":"12","acknowledgement":"AA was supported by European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (Grant Agreement No. 78818 Alpha). RK was supported by the Federal professorship program Grant 1.456.2016/1.4 and the Russian Foundation for Basic Research Grants 18-01-00036 and 19-01-00169. Open access funding provided by Institute of Science and Technology (IST Austria). The authors thank Alexey Balitskiy, Milena Radnović, and Serge Tabachnikov for useful discussions.","citation":{"mla":"Akopyan, Arseniy, and Roman Karasev. “When Different Norms Lead to Same Billiard Trajectories?” European Journal of Mathematics, vol. 8, no. 4, Springer Nature, 2022, pp. 1309–12, doi:10.1007/s40879-020-00405-0.","short":"A. Akopyan, R. Karasev, European Journal of Mathematics 8 (2022) 1309–1312.","ieee":"A. Akopyan and R. Karasev, “When different norms lead to same billiard trajectories?,” European Journal of Mathematics, vol. 8, no. 4. Springer Nature, pp. 1309–1312, 2022.","chicago":"Akopyan, Arseniy, and Roman Karasev. “When Different Norms Lead to Same Billiard Trajectories?” European Journal of Mathematics. Springer Nature, 2022. https://doi.org/10.1007/s40879-020-00405-0.","ista":"Akopyan A, Karasev R. 2022. When different norms lead to same billiard trajectories? European Journal of Mathematics. 8(4), 1309–1312.","ama":"Akopyan A, Karasev R. When different norms lead to same billiard trajectories? European Journal of Mathematics. 2022;8(4):1309-1312. doi:10.1007/s40879-020-00405-0","apa":"Akopyan, A., & Karasev, R. (2022). When different norms lead to same billiard trajectories? European Journal of Mathematics. Springer Nature. https://doi.org/10.1007/s40879-020-00405-0"},"issue":"4","_id":"7791","volume":8,"file":[{"creator":"dernst","file_size":263926,"file_name":"2020_EuropMathematics_Akopyan.pdf","checksum":"f53e71fd03744075adcd0b8fc1b8423d","file_id":"7796","date_updated":"2020-07-14T12:48:03Z","relation":"main_file","access_level":"open_access","date_created":"2020-05-04T10:33:42Z","content_type":"application/pdf"}],"project":[{"_id":"266A2E9E-B435-11E9-9278-68D0E5697425","grant_number":"788183","name":"Alpha Shape Theory Extended","call_identifier":"H2020"},{"_id":"B67AFEDC-15C9-11EA-A837-991A96BB2854","name":"IST Austria Open Access Fund"}],"doi":"10.1007/s40879-020-00405-0","date_published":"2022-12-01T00:00:00Z","title":"When different norms lead to same billiard trajectories?","day":"01","publication":"European Journal of Mathematics","quality_controlled":"1","type":"journal_article","scopus_import":"1","publication_status":"published","publisher":"Springer Nature","has_accepted_license":"1","arxiv":1,"oa_version":"Published Version","status":"public","page":"1309 - 1312","author":[{"first_name":"Arseniy","id":"430D2C90-F248-11E8-B48F-1D18A9856A87","full_name":"Akopyan, Arseniy","last_name":"Akopyan","orcid":"0000-0002-2548-617X"},{"first_name":"Roman","full_name":"Karasev, Roman","last_name":"Karasev"}],"year":"2022","tmp":{"short":"CC BY (4.0)","image":"/images/cc_by.png","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode"},"ec_funded":1,"publication_identifier":{"issn":["2199-675X"],"eissn":["2199-6768"]},"language":[{"iso":"eng"}],"ddc":["510"],"oa":1,"external_id":{"arxiv":["1912.12685"]},"abstract":[{"lang":"eng","text":"Extending a result of Milena Radnovic and Serge Tabachnikov, we establish conditionsfor two different non-symmetric norms to define the same billiard reflection law."}],"article_processing_charge":"Yes (via OA deal)","user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87","file_date_updated":"2020-07-14T12:48:03Z"},{"main_file_link":[{"url":"https://doi.org/10.1101/2020.01.08.898528 ","open_access":"1"}],"doi":"10.1101/2020.01.08.898528","_id":"8125","year":"2022","month":"12","author":[{"first_name":"William F.","last_name":"Podlaski","full_name":"Podlaski, William F.","orcid":"0000-0001-6619-7502"},{"orcid":"0000-0001-7184-7311","last_name":"Agnes","full_name":"Agnes, Everton J.","first_name":"Everton J."},{"full_name":"Vogels, Tim P","last_name":"Vogels","orcid":"0000-0003-3295-6181","id":"CB6FF8D2-008F-11EA-8E08-2637E6697425","first_name":"Tim P"}],"citation":{"ieee":"W. F. Podlaski, E. J. Agnes, and T. P. Vogels, “High capacity and dynamic accessibility in associative memory networks with context-dependent neuronal and synaptic gating,” bioRxiv. Cold Spring Harbor Laboratory, 2022.","mla":"Podlaski, William F., et al. “High Capacity and Dynamic Accessibility in Associative Memory Networks with Context-Dependent Neuronal and Synaptic Gating.” BioRxiv, Cold Spring Harbor Laboratory, 2022, doi:10.1101/2020.01.08.898528.","short":"W.F. Podlaski, E.J. Agnes, T.P. Vogels, BioRxiv (2022).","chicago":"Podlaski, William F., Everton J. Agnes, and Tim P Vogels. “High Capacity and Dynamic Accessibility in Associative Memory Networks with Context-Dependent Neuronal and Synaptic Gating.” BioRxiv. Cold Spring Harbor Laboratory, 2022. https://doi.org/10.1101/2020.01.08.898528.","ista":"Podlaski WF, Agnes EJ, Vogels TP. 2022. High capacity and dynamic accessibility in associative memory networks with context-dependent neuronal and synaptic gating. bioRxiv, 10.1101/2020.01.08.898528.","apa":"Podlaski, W. F., Agnes, E. J., & Vogels, T. P. (2022). High capacity and dynamic accessibility in associative memory networks with context-dependent neuronal and synaptic gating. bioRxiv. Cold Spring Harbor Laboratory. https://doi.org/10.1101/2020.01.08.898528","ama":"Podlaski WF, Agnes EJ, Vogels TP. High capacity and dynamic accessibility in associative memory networks with context-dependent neuronal and synaptic gating. bioRxiv. 2022. doi:10.1101/2020.01.08.898528"},"date_created":"2020-07-16T12:24:28Z","date_updated":"2024-03-06T12:03:59Z","oa_version":"Preprint","department":[{"_id":"TiVo"}],"status":"public","type":"preprint","publication_status":"published","abstract":[{"lang":"eng","text":"Context, such as behavioral state, is known to modulate memory formation and retrieval, but is usually ignored in associative memory models. Here, we propose several types of contextual modulation for associative memory networks that greatly increase their performance. In these networks, context inactivates specific neurons and connections, which modulates the effective connectivity of the network. Memories are stored only by the active components, thereby reducing interference from memories acquired in other contexts. Such networks exhibit several beneficial characteristics, including enhanced memory capacity, high robustness to noise, increased robustness to memory overloading, and better memory retention during continual learning. Furthermore, memories can be biased to have different relative strengths, or even gated on or off, according to contextual cues, providing a candidate model for cognitive control of memory and efficient memory search. An external context-encoding network can dynamically switch the memory network to a desired state, which we liken to experimentally observed contextual signals in prefrontal cortex and hippocampus. Overall, our work illustrates the benefits of organizing memory around context, and provides an important link between behavioral studies of memory and mechanistic details of neural circuits.SIGNIFICANCEMemory is context dependent — both encoding and recall vary in effectiveness and speed depending on factors like location and brain state during a task. We apply this idea to a simple computational model of associative memory through contextual gating of neurons and synaptic connections. Intriguingly, this results in several advantages, including vastly enhanced memory capacity, better robustness, and flexible memory gating. Our model helps to explain (i) how gating and inhibition contribute to memory processes, (ii) how memory access dynamically changes over time, and (iii) how context representations, such as those observed in hippocampus and prefrontal cortex, may interact with and control memory processes."}],"article_processing_charge":"No","publisher":"Cold Spring Harbor Laboratory","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","oa":1,"date_published":"2022-12-21T00:00:00Z","locked":"1","title":"High capacity and dynamic accessibility in associative memory networks with context-dependent neuronal and synaptic gating","day":"21","publication":"bioRxiv","language":[{"iso":"eng"}]},{"article_number":"2210.01738","arxiv":1,"publication_status":"submitted","type":"preprint","external_id":{"arxiv":["2210.01738"]},"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","abstract":[{"lang":"eng","text":"CLIP proved that aligning visual and language spaces is key to solving many vision tasks without explicit training, but required to train image and text encoders from scratch on a huge dataset. LiT improved this by only training the text encoder and using a pre-trained vision network. In this paper, we show that a common space can be created without any training at all, using single-domain encoders (trained with or without supervision) and a much smaller amount of image-text pairs. Furthermore, our model has unique properties. Most notably, deploying a new version with updated training samples can be done in a matter of seconds. Additionally, the representations in the common space are easily interpretable as every dimension corresponds to the similarity of the input to a unique entry in the multimodal dataset. Experiments on standard zero-shot visual benchmarks demonstrate the typical transfer ability of image-text models. Overall, our method represents a simple yet surprisingly strong baseline for foundation multi-modal models, raising important questions on their data efficiency and on the role of retrieval in machine learning."}],"article_processing_charge":"No","oa":1,"day":"04","date_published":"2022-10-04T00:00:00Z","title":"ASIF: Coupled data turns unimodal models to multimodal without training","language":[{"iso":"eng"}],"publication":"arXiv","main_file_link":[{"open_access":"1","url":"https://doi.org/10.48550/arXiv.2210.01738"}],"doi":"10.48550/arXiv.2210.01738","year":"2022","_id":"14216","author":[{"first_name":"Antonio","full_name":"Norelli, Antonio","last_name":"Norelli"},{"first_name":"Marco","full_name":"Fumero, Marco","last_name":"Fumero"},{"first_name":"Valentino","full_name":"Maiorca, Valentino","last_name":"Maiorca"},{"first_name":"Luca","last_name":"Moschella","full_name":"Moschella, Luca"},{"full_name":"Rodolà, Emanuele","last_name":"Rodolà","first_name":"Emanuele"},{"orcid":"0000-0002-4850-0683","full_name":"Locatello, Francesco","last_name":"Locatello","id":"26cfd52f-2483-11ee-8040-88983bcc06d4","first_name":"Francesco"}],"month":"10","citation":{"short":"A. Norelli, M. Fumero, V. Maiorca, L. Moschella, E. Rodolà, F. Locatello, ArXiv (n.d.).","mla":"Norelli, Antonio, et al. “ASIF: Coupled Data Turns Unimodal Models to Multimodal without Training.” ArXiv, 2210.01738, doi:10.48550/arXiv.2210.01738.","ieee":"A. Norelli, M. Fumero, V. Maiorca, L. Moschella, E. Rodolà, and F. Locatello, “ASIF: Coupled data turns unimodal models to multimodal without training,” arXiv. .","chicago":"Norelli, Antonio, Marco Fumero, Valentino Maiorca, Luca Moschella, Emanuele Rodolà, and Francesco Locatello. “ASIF: Coupled Data Turns Unimodal Models to Multimodal without Training.” ArXiv, n.d. https://doi.org/10.48550/arXiv.2210.01738.","ista":"Norelli A, Fumero M, Maiorca V, Moschella L, Rodolà E, Locatello F. ASIF: Coupled data turns unimodal models to multimodal without training. arXiv, 2210.01738.","ama":"Norelli A, Fumero M, Maiorca V, Moschella L, Rodolà E, Locatello F. ASIF: Coupled data turns unimodal models to multimodal without training. arXiv. doi:10.48550/arXiv.2210.01738","apa":"Norelli, A., Fumero, M., Maiorca, V., Moschella, L., Rodolà, E., & Locatello, F. (n.d.). ASIF: Coupled data turns unimodal models to multimodal without training. arXiv. https://doi.org/10.48550/arXiv.2210.01738"},"oa_version":"Preprint","department":[{"_id":"FrLo"}],"date_updated":"2024-02-12T09:57:14Z","date_created":"2023-08-22T14:22:04Z","status":"public"},{"date_updated":"2023-10-03T08:04:03Z","date_created":"2023-10-01T22:01:14Z","oa_version":"None","department":[{"_id":"UlWa"}],"status":"public","intvolume":" 438","month":"01","page":"281-294","article_type":"original","author":[{"orcid":"0000-0002-1494-0568","last_name":"Wagner","full_name":"Wagner, Uli","id":"36690CA2-F248-11E8-B48F-1D18A9856A87","first_name":"Uli"}],"citation":{"chicago":"Wagner, Uli. “High-Dimensional Expanders (after Gromov, Kaufman, Kazhdan, Lubotzky, and Others).” Bulletin de La Societe Mathematique de France. Societe Mathematique de France, 2022. https://doi.org/10.24033/ast.1188.","mla":"Wagner, Uli. “High-Dimensional Expanders (after Gromov, Kaufman, Kazhdan, Lubotzky, and Others).” Bulletin de La Societe Mathematique de France, vol. 438, Societe Mathematique de France, 2022, pp. 281–94, doi:10.24033/ast.1188.","short":"U. Wagner, Bulletin de La Societe Mathematique de France 438 (2022) 281–294.","ieee":"U. Wagner, “High-dimensional expanders (after Gromov, Kaufman, Kazhdan, Lubotzky, and others),” Bulletin de la Societe Mathematique de France, vol. 438. Societe Mathematique de France, pp. 281–294, 2022.","ama":"Wagner U. High-dimensional expanders (after Gromov, Kaufman, Kazhdan, Lubotzky, and others). Bulletin de la Societe Mathematique de France. 2022;438:281-294. doi:10.24033/ast.1188","apa":"Wagner, U. (2022). High-dimensional expanders (after Gromov, Kaufman, Kazhdan, Lubotzky, and others). Bulletin de La Societe Mathematique de France. Societe Mathematique de France. https://doi.org/10.24033/ast.1188","ista":"Wagner U. 2022. High-dimensional expanders (after Gromov, Kaufman, Kazhdan, Lubotzky, and others). Bulletin de la Societe Mathematique de France. 438, 281–294."},"_id":"14381","year":"2022","volume":438,"publication_identifier":{"issn":["0037-9484"],"eissn":["2102-622X"]},"doi":"10.24033/ast.1188","title":"High-dimensional expanders (after Gromov, Kaufman, Kazhdan, Lubotzky, and others)","date_published":"2022-01-01T00:00:00Z","day":"01","language":[{"iso":"eng"}],"publication":"Bulletin de la Societe Mathematique de France","scopus_import":"1","publication_status":"published","type":"journal_article","quality_controlled":"1","abstract":[{"lang":"eng","text":"Expander graphs (sparse but highly connected graphs) have, since their inception, been the source of deep links between Mathematics and Computer Science as well as applications to other areas. In recent years, a fascinating theory of high-dimensional expanders has begun to emerge, which is still in a formative stage but has nonetheless already lead to a number of striking results. Unlike for graphs, in higher dimensions there is a rich array of non-equivalent notions of expansion (coboundary expansion, cosystolic expansion, topological expansion, spectral expansion, etc.), with differents strengths and applications. In this talk, we will survey this landscape of high-dimensional expansion, with a focus on two main results. First, we will present Gromov’s Topological Overlap Theorem, which asserts that coboundary expansion (a quantitative version of vanishing mod 2 cohomology) implies topological expansion (roughly, the property that for every map from a simplicial complex to a manifold of the same dimension, the images of a positive fraction of the simplices have a point in common). Second, we will outline a construction of bounded degree 2-dimensional topological expanders, due to Kaufman, Kazhdan, and Lubotzky."}],"article_processing_charge":"No","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","publisher":"Societe Mathematique de France"},{"keyword":["Multidisciplinary"],"day":"21","title":"Molecular engineering enables bright blue LEDs","date_published":"2022-12-21T00:00:00Z","publication":"Nature","type":"journal_article","quality_controlled":"1","publication_status":"published","publisher":"Springer Nature","department":[{"_id":"MaIb"}],"date_created":"2023-10-17T11:14:43Z","date_updated":"2023-10-18T06:26:30Z","intvolume":" 612","month":"12","article_type":"letter_note","citation":{"chicago":"Utzat, Hendrik, and Maria Ibáñez. “Molecular Engineering Enables Bright Blue LEDs.” Nature. Springer Nature, 2022. https://doi.org/10.1038/d41586-022-04447-0.","ieee":"H. Utzat and M. Ibáñez, “Molecular engineering enables bright blue LEDs,” Nature, vol. 612, no. 7941. Springer Nature, pp. 638–639, 2022.","mla":"Utzat, Hendrik, and Maria Ibáñez. “Molecular Engineering Enables Bright Blue LEDs.” Nature, vol. 612, no. 7941, Springer Nature, 2022, pp. 638–39, doi:10.1038/d41586-022-04447-0.","short":"H. Utzat, M. Ibáñez, Nature 612 (2022) 638–639.","apa":"Utzat, H., & Ibáñez, M. (2022). Molecular engineering enables bright blue LEDs. Nature. Springer Nature. https://doi.org/10.1038/d41586-022-04447-0","ama":"Utzat H, Ibáñez M. Molecular engineering enables bright blue LEDs. Nature. 2022;612(7941):638-639. doi:10.1038/d41586-022-04447-0","ista":"Utzat H, Ibáñez M. 2022. Molecular engineering enables bright blue LEDs. Nature. 612(7941), 638–639."},"issue":"7941","_id":"14437","volume":612,"doi":"10.1038/d41586-022-04447-0","pmid":1,"language":[{"iso":"eng"}],"external_id":{"pmid":["36543947"]},"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","article_processing_charge":"No","abstract":[{"lang":"eng","text":"Future LEDs could be based on lead halide perovskites. A breakthrough in preparing device-compatible solids composed of nanoscale perovskite crystals overcomes a long-standing hurdle in making blue perovskite LEDs."}],"oa_version":"None","status":"public","author":[{"last_name":"Utzat","full_name":"Utzat, Hendrik","first_name":"Hendrik"},{"id":"43C61214-F248-11E8-B48F-1D18A9856A87","first_name":"Maria","orcid":"0000-0001-5013-2843","full_name":"Ibáñez, Maria","last_name":"Ibáñez"}],"page":"638-639","year":"2022","publication_identifier":{"issn":["0028-0836"],"eissn":["1476-4687"]}},{"main_file_link":[{"url":"https://doi.org/10.5281/ZENODO.8408897","open_access":"1"}],"tmp":{"image":"/images/cc_0.png","short":"CC0 (1.0)","legal_code_url":"https://creativecommons.org/publicdomain/zero/1.0/legalcode","name":"Creative Commons Public Domain Dedication (CC0 1.0)"},"doi":"10.5281/ZENODO.8408897","year":"2022","_id":"14520","month":"06","author":[{"full_name":"Zemlicka, Martin","last_name":"Zemlicka","first_name":"Martin","id":"2DCF8DE6-F248-11E8-B48F-1D18A9856A87"},{"first_name":"Elena","id":"2C21D6E8-F248-11E8-B48F-1D18A9856A87","full_name":"Redchenko, Elena","last_name":"Redchenko"},{"first_name":"Matilda","id":"3F920B30-F248-11E8-B48F-1D18A9856A87","last_name":"Peruzzo","full_name":"Peruzzo, Matilda","orcid":"0000-0002-3415-4628"},{"first_name":"Farid","id":"2AED110C-F248-11E8-B48F-1D18A9856A87","last_name":"Hassani","full_name":"Hassani, Farid","orcid":"0000-0001-6937-5773"},{"last_name":"Trioni","full_name":"Trioni, Andrea","id":"42F71B44-F248-11E8-B48F-1D18A9856A87","first_name":"Andrea"},{"full_name":"Barzanjeh, Shabir","last_name":"Barzanjeh","orcid":"0000-0003-0415-1423","first_name":"Shabir","id":"2D25E1F6-F248-11E8-B48F-1D18A9856A87"},{"id":"4B591CBA-F248-11E8-B48F-1D18A9856A87","first_name":"Johannes M","orcid":"0000-0001-8112-028X","full_name":"Fink, Johannes M","last_name":"Fink"}],"related_material":{"record":[{"relation":"used_in_publication","status":"public","id":"14517"}]},"citation":{"apa":"Zemlicka, M., Redchenko, E., Peruzzo, M., Hassani, F., Trioni, A., Barzanjeh, S., & Fink, J. M. (2022). Compact vacuum gap transmon qubits: Selective and sensitive probes for superconductor surface losses. Zenodo. https://doi.org/10.5281/ZENODO.8408897","ama":"Zemlicka M, Redchenko E, Peruzzo M, et al. Compact vacuum gap transmon qubits: Selective and sensitive probes for superconductor surface losses. 2022. doi:10.5281/ZENODO.8408897","ista":"Zemlicka M, Redchenko E, Peruzzo M, Hassani F, Trioni A, Barzanjeh S, Fink JM. 2022. Compact vacuum gap transmon qubits: Selective and sensitive probes for superconductor surface losses, Zenodo, 10.5281/ZENODO.8408897.","chicago":"Zemlicka, Martin, Elena Redchenko, Matilda Peruzzo, Farid Hassani, Andrea Trioni, Shabir Barzanjeh, and Johannes M Fink. “Compact Vacuum Gap Transmon Qubits: Selective and Sensitive Probes for Superconductor Surface Losses.” Zenodo, 2022. https://doi.org/10.5281/ZENODO.8408897.","ieee":"M. Zemlicka et al., “Compact vacuum gap transmon qubits: Selective and sensitive probes for superconductor surface losses.” Zenodo, 2022.","short":"M. Zemlicka, E. Redchenko, M. Peruzzo, F. Hassani, A. Trioni, S. Barzanjeh, J.M. Fink, (2022).","mla":"Zemlicka, Martin, et al. Compact Vacuum Gap Transmon Qubits: Selective and Sensitive Probes for Superconductor Surface Losses. Zenodo, 2022, doi:10.5281/ZENODO.8408897."},"date_updated":"2024-09-10T12:23:57Z","date_created":"2023-11-13T08:09:10Z","department":[{"_id":"JoFi"}],"oa_version":"Published Version","status":"public","has_accepted_license":"1","type":"research_data_reference","abstract":[{"text":"This dataset comprises all data shown in the figures of the submitted article \"Compact vacuum gap transmon qubits: Selective and sensitive probes for superconductor surface losses\" at arxiv.org/abs/2206.14104. Additional raw data are available from the corresponding author on reasonable request.","lang":"eng"}],"article_processing_charge":"No","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","publisher":"Zenodo","ddc":["530"],"oa":1,"date_published":"2022-06-28T00:00:00Z","title":"Compact vacuum gap transmon qubits: Selective and sensitive probes for superconductor surface losses","day":"28"},{"citation":{"mla":"Fischer, Julian L., and Alice Marveggio. “Quantitative Convergence of the Vectorial Allen-Cahn Equation towards Multiphase Mean Curvature Flow.” ArXiv, doi:10.48550/ARXIV.2203.17143.","short":"J.L. Fischer, A. Marveggio, ArXiv (n.d.).","ieee":"J. L. Fischer and A. Marveggio, “Quantitative convergence of the vectorial Allen-Cahn equation towards multiphase mean curvature flow,” arXiv. .","chicago":"Fischer, Julian L, and Alice Marveggio. “Quantitative Convergence of the Vectorial Allen-Cahn Equation towards Multiphase Mean Curvature Flow.” ArXiv, n.d. https://doi.org/10.48550/ARXIV.2203.17143.","ista":"Fischer JL, Marveggio A. Quantitative convergence of the vectorial Allen-Cahn equation towards multiphase mean curvature flow. arXiv, 10.48550/ARXIV.2203.17143.","ama":"Fischer JL, Marveggio A. Quantitative convergence of the vectorial Allen-Cahn equation towards multiphase mean curvature flow. arXiv. doi:10.48550/ARXIV.2203.17143","apa":"Fischer, J. L., & Marveggio, A. (n.d.). Quantitative convergence of the vectorial Allen-Cahn equation towards multiphase mean curvature flow. arXiv. https://doi.org/10.48550/ARXIV.2203.17143"},"related_material":{"record":[{"id":"14587","status":"public","relation":"dissertation_contains"}]},"author":[{"first_name":"Julian L","id":"2C12A0B0-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-0479-558X","last_name":"Fischer","full_name":"Fischer, Julian L"},{"last_name":"Marveggio","full_name":"Marveggio, Alice","first_name":"Alice","id":"25647992-AA84-11E9-9D75-8427E6697425"}],"month":"03","status":"public","oa_version":"Preprint","department":[{"_id":"JuFi"}],"date_created":"2023-11-23T09:30:02Z","date_updated":"2023-11-30T13:25:02Z","doi":"10.48550/ARXIV.2203.17143","project":[{"_id":"0aa76401-070f-11eb-9043-b5bb049fa26d","name":"Bridging Scales in Random Materials","grant_number":"948819","call_identifier":"H2020"}],"ec_funded":1,"main_file_link":[{"open_access":"1","url":"https://arxiv.org/abs/2203.17143"}],"year":"2022","_id":"14597","oa":1,"publication":"arXiv","language":[{"iso":"eng"}],"day":"31","title":"Quantitative convergence of the vectorial Allen-Cahn equation towards multiphase mean curvature flow","date_published":"2022-03-31T00:00:00Z","arxiv":1,"user_id":"8b945eb4-e2f2-11eb-945a-df72226e66a9","abstract":[{"text":"Phase-field models such as the Allen-Cahn equation may give rise to the formation and evolution of geometric shapes, a phenomenon that may be analyzed rigorously in suitable scaling regimes. In its sharp-interface limit, the vectorial Allen-Cahn equation with a potential with N≥3 distinct minima has been conjectured to describe the evolution of branched interfaces by multiphase mean curvature flow.\r\nIn the present work, we give a rigorous proof for this statement in two and three ambient dimensions and for a suitable class of potentials: As long as a strong solution to multiphase mean curvature flow exists, solutions to the vectorial Allen-Cahn equation with well-prepared initial data converge towards multiphase mean curvature flow in the limit of vanishing interface width parameter ε↘0. We even establish the rate of convergence O(ε1/2).\r\nOur approach is based on the gradient flow structure of the Allen-Cahn equation and its limiting motion: Building on the recent concept of \"gradient flow calibrations\" for multiphase mean curvature flow, we introduce a notion of relative entropy for the vectorial Allen-Cahn equation with multi-well potential. This enables us to overcome the limitations of other approaches, e.g. avoiding the need for a stability analysis of the Allen-Cahn operator or additional convergence hypotheses for the energy at positive times.","lang":"eng"}],"article_processing_charge":"No","publication_status":"submitted","type":"preprint","external_id":{"arxiv":["2203.17143"]}},{"oa":1,"language":[{"iso":"eng"}],"publication":"arXiv","day":"29","title":"Learning control policies for stochastic systems with reach-avoid guarantees","date_published":"2022-11-29T00:00:00Z","arxiv":1,"user_id":"8b945eb4-e2f2-11eb-945a-df72226e66a9","article_processing_charge":"No","abstract":[{"text":"We study the problem of learning controllers for discrete-time non-linear stochastic dynamical systems with formal reach-avoid guarantees. This work presents the first method for providing formal reach-avoid guarantees, which combine and generalize stability and safety guarantees, with a tolerable probability threshold $p\\in[0,1]$ over the infinite time horizon. Our method leverages advances in machine learning literature and it represents formal certificates as neural networks. In particular, we learn a certificate in the form of a reach-avoid supermartingale (RASM), a novel notion that we introduce in this work. Our RASMs provide reachability and avoidance guarantees by imposing constraints on what can be viewed as a stochastic extension of level sets of Lyapunov functions for deterministic systems. Our approach solves several important problems -- it can be used to learn a control policy from scratch, to verify a reach-avoid specification for a fixed control policy, or to fine-tune a pre-trained policy if it does not satisfy the reach-avoid specification. We validate our approach on $3$ stochastic non-linear reinforcement learning tasks.","lang":"eng"}],"publication_status":"submitted","type":"preprint","external_id":{"arxiv":["2210.05308"]},"citation":{"ista":"Zikelic D, Lechner M, Henzinger TA, Chatterjee K. Learning control policies for stochastic systems with reach-avoid guarantees. arXiv, 10.48550/ARXIV.2210.05308.","ama":"Zikelic D, Lechner M, Henzinger TA, Chatterjee K. Learning control policies for stochastic systems with reach-avoid guarantees. arXiv. doi:10.48550/ARXIV.2210.05308","apa":"Zikelic, D., Lechner, M., Henzinger, T. A., & Chatterjee, K. (n.d.). Learning control policies for stochastic systems with reach-avoid guarantees. arXiv. https://doi.org/10.48550/ARXIV.2210.05308","mla":"Zikelic, Dorde, et al. “Learning Control Policies for Stochastic Systems with Reach-Avoid Guarantees.” ArXiv, doi:10.48550/ARXIV.2210.05308.","short":"D. Zikelic, M. Lechner, T.A. Henzinger, K. Chatterjee, ArXiv (n.d.).","ieee":"D. Zikelic, M. Lechner, T. A. Henzinger, and K. Chatterjee, “Learning control policies for stochastic systems with reach-avoid guarantees,” arXiv. .","chicago":"Zikelic, Dorde, Mathias Lechner, Thomas A Henzinger, and Krishnendu Chatterjee. “Learning Control Policies for Stochastic Systems with Reach-Avoid Guarantees.” ArXiv, n.d. https://doi.org/10.48550/ARXIV.2210.05308."},"related_material":{"record":[{"status":"public","relation":"dissertation_contains","id":"14539"},{"id":"14830","status":"public","relation":"later_version"}]},"author":[{"first_name":"Dorde","id":"294AA7A6-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-4681-1699","last_name":"Zikelic","full_name":"Zikelic, Dorde"},{"first_name":"Mathias","id":"3DC22916-F248-11E8-B48F-1D18A9856A87","last_name":"Lechner","full_name":"Lechner, Mathias"},{"id":"40876CD8-F248-11E8-B48F-1D18A9856A87","first_name":"Thomas A","full_name":"Henzinger, Thomas A","last_name":"Henzinger","orcid":"0000-0002-2985-7724"},{"first_name":"Krishnendu","id":"2E5DCA20-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-4561-241X","full_name":"Chatterjee, Krishnendu","last_name":"Chatterjee"}],"month":"11","status":"public","department":[{"_id":"KrCh"},{"_id":"ToHe"}],"oa_version":"Preprint","date_updated":"2025-07-14T09:10:02Z","date_created":"2023-11-24T13:10:09Z","doi":"10.48550/ARXIV.2210.05308","project":[{"_id":"0599E47C-7A3F-11EA-A408-12923DDC885E","name":"Formal Methods for Stochastic Models: Algorithms and Applications","grant_number":"863818","call_identifier":"H2020"},{"call_identifier":"H2020","grant_number":"101020093","name":"Vigilant Algorithmic Monitoring of Software","_id":"62781420-2b32-11ec-9570-8d9b63373d4d"},{"call_identifier":"H2020","grant_number":"665385","name":"International IST Doctoral Program","_id":"2564DBCA-B435-11E9-9278-68D0E5697425"}],"ec_funded":1,"tmp":{"name":"Creative Commons Attribution-ShareAlike 4.0 International Public License (CC BY-SA 4.0)","legal_code_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","image":"/images/cc_by_sa.png","short":"CC BY-SA (4.0)"},"main_file_link":[{"url":"https://arxiv.org/abs/2210.05308","open_access":"1"}],"_id":"14600","year":"2022"},{"_id":"14601","year":"2022","main_file_link":[{"url":"https://arxiv.org/abs/2205.11991","open_access":"1"}],"ec_funded":1,"project":[{"_id":"62781420-2b32-11ec-9570-8d9b63373d4d","name":"Vigilant Algorithmic Monitoring of Software","grant_number":"101020093","call_identifier":"H2020"},{"_id":"0599E47C-7A3F-11EA-A408-12923DDC885E","call_identifier":"H2020","grant_number":"863818","name":"Formal Methods for Stochastic Models: Algorithms and Applications"},{"_id":"2564DBCA-B435-11E9-9278-68D0E5697425","call_identifier":"H2020","grant_number":"665385","name":"International IST Doctoral Program"}],"doi":"10.48550/arXiv.2205.11991","date_created":"2023-11-24T13:22:30Z","date_updated":"2025-07-14T09:10:00Z","oa_version":"Preprint","department":[{"_id":"KrCh"},{"_id":"ToHe"}],"status":"public","month":"05","author":[{"first_name":"Dorde","id":"294AA7A6-F248-11E8-B48F-1D18A9856A87","full_name":"Zikelic, Dorde","last_name":"Zikelic","orcid":"0000-0002-4681-1699"},{"last_name":"Lechner","full_name":"Lechner, Mathias","id":"3DC22916-F248-11E8-B48F-1D18A9856A87","first_name":"Mathias"},{"orcid":"0000-0002-4561-241X","last_name":"Chatterjee","full_name":"Chatterjee, Krishnendu","id":"2E5DCA20-F248-11E8-B48F-1D18A9856A87","first_name":"Krishnendu"},{"orcid":"0000-0002-2985-7724","last_name":"Henzinger","full_name":"Henzinger, Thomas A","first_name":"Thomas A","id":"40876CD8-F248-11E8-B48F-1D18A9856A87"}],"related_material":{"record":[{"status":"public","relation":"dissertation_contains","id":"14539"}]},"citation":{"apa":"Zikelic, D., Lechner, M., Chatterjee, K., & Henzinger, T. A. (n.d.). Learning stabilizing policies in stochastic control systems. arXiv. https://doi.org/10.48550/arXiv.2205.11991","ama":"Zikelic D, Lechner M, Chatterjee K, Henzinger TA. Learning stabilizing policies in stochastic control systems. arXiv. doi:10.48550/arXiv.2205.11991","ista":"Zikelic D, Lechner M, Chatterjee K, Henzinger TA. Learning stabilizing policies in stochastic control systems. arXiv, 10.48550/arXiv.2205.11991.","chicago":"Zikelic, Dorde, Mathias Lechner, Krishnendu Chatterjee, and Thomas A Henzinger. “Learning Stabilizing Policies in Stochastic Control Systems.” ArXiv, n.d. https://doi.org/10.48550/arXiv.2205.11991.","ieee":"D. Zikelic, M. Lechner, K. Chatterjee, and T. A. Henzinger, “Learning stabilizing policies in stochastic control systems,” arXiv. .","short":"D. Zikelic, M. Lechner, K. Chatterjee, T.A. Henzinger, ArXiv (n.d.).","mla":"Zikelic, Dorde, et al. “Learning Stabilizing Policies in Stochastic Control Systems.” ArXiv, doi:10.48550/arXiv.2205.11991."},"external_id":{"arxiv":["2205.11991"]},"publication_status":"submitted","type":"preprint","article_processing_charge":"No","abstract":[{"text":"In this work, we address the problem of learning provably stable neural\r\nnetwork policies for stochastic control systems. While recent work has\r\ndemonstrated the feasibility of certifying given policies using martingale\r\ntheory, the problem of how to learn such policies is little explored. Here, we\r\nstudy the effectiveness of jointly learning a policy together with a martingale\r\ncertificate that proves its stability using a single learning algorithm. We\r\nobserve that the joint optimization problem becomes easily stuck in local\r\nminima when starting from a randomly initialized policy. Our results suggest\r\nthat some form of pre-training of the policy is required for the joint\r\noptimization to repair and verify the policy successfully.","lang":"eng"}],"user_id":"8b945eb4-e2f2-11eb-945a-df72226e66a9","arxiv":1,"date_published":"2022-05-24T00:00:00Z","title":"Learning stabilizing policies in stochastic control systems","day":"24","publication":"arXiv","language":[{"iso":"eng"}],"oa":1}]