--- _id: '12894' 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" article_processing_charge: No author: - first_name: Alois full_name: Schlögl, Alois id: 45BF87EE-F248-11E8-B48F-1D18A9856A87 last_name: Schlögl orcid: 0000-0002-5621-8100 - first_name: Andrei full_name: Hornoiu, Andrei id: 77129392-B450-11EA-8745-D4653DDC885E last_name: Hornoiu - first_name: Stefano full_name: Elefante, Stefano id: 490F40CE-F248-11E8-B48F-1D18A9856A87 last_name: Elefante - first_name: Stephan full_name: Stadlbauer, Stephan id: 4D0BC184-F248-11E8-B48F-1D18A9856A87 last_name: Stadlbauer 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' 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. 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. 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.' 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. conference: end_date: 2022-06-02 location: Grundlsee, Austria name: 'ASHPC: Austrian-Slovenian HPC Meeting' start_date: 2022-05-31 date_created: 2023-05-05T09:13:42Z date_published: 2022-06-02T00:00:00Z date_updated: 2023-05-16T07:42:56Z day: '02' ddc: - '000' department: - _id: ScienComp doi: 10.25365/phaidra.337 file: - access_level: open_access checksum: e3f8c240b85422ce2190e7b203cc2563 content_type: application/pdf creator: schloegl date_created: 2023-05-05T09:06:00Z date_updated: 2023-05-05T09:06:00Z file_id: '12895' file_name: BOOKLET_ASHPC22.pdf file_size: 7180531 relation: main_file success: 1 file_date_updated: 2023-05-05T09:06:00Z has_accepted_license: '1' language: - iso: eng month: '06' oa: 1 oa_version: Published Version page: '7' publication: ASHPC22 - Austrian-Slovenian HPC Meeting 2022 publication_identifier: isbn: - 978-3-200-08499-5 publication_status: published publisher: EuroCC Austria c/o Universität Wien status: public title: Where is the sweet spot? A procurement story of general purpose compute nodes tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: conference_abstract user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 year: '2022' ... --- _id: '13064' abstract: - lang: eng 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. article_processing_charge: No author: - first_name: Etienne full_name: Orliac, Etienne last_name: Orliac - first_name: Daniel full_name: Trejo Banos, Daniel last_name: Trejo Banos - first_name: Sven full_name: Ojavee, Sven last_name: Ojavee - first_name: Kristi full_name: Läll, Kristi last_name: Läll - first_name: Reedik full_name: Mägi, Reedik last_name: Mägi - first_name: Peter full_name: Visscher, Peter last_name: Visscher - first_name: Matthew Richard full_name: Robinson, Matthew Richard id: E5D42276-F5DA-11E9-8E24-6303E6697425 last_name: Robinson orcid: 0000-0001-8982-8813 citation: 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 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. ieee: E. Orliac et al., “Improving genome-wide association discovery and genomic prediction accuracy in biobank data.” Dryad, 2022. 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. 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). date_created: 2023-05-23T16:28:13Z date_published: 2022-09-02T00:00:00Z date_updated: 2023-08-03T12:40:37Z day: '02' ddc: - '570' department: - _id: MaRo doi: 10.5061/DRYAD.GTHT76HMZ license: https://creativecommons.org/publicdomain/zero/1.0/ main_file_link: - open_access: '1' url: https://doi.org/10.5061/dryad.gtht76hmz month: '09' oa: 1 oa_version: Published Version publisher: Dryad related_material: record: - id: '11733' relation: used_in_publication status: public status: public title: Improving genome-wide association discovery and genomic prediction accuracy in biobank data tmp: image: /images/cc_0.png legal_code_url: https://creativecommons.org/publicdomain/zero/1.0/legalcode name: Creative Commons Public Domain Dedication (CC0 1.0) short: CC0 (1.0) type: research_data_reference user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 year: '2022' ... --- _id: '13066' abstract: - lang: eng 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. article_processing_charge: No author: - first_name: Eva full_name: Koch, Eva last_name: Koch - first_name: Mark full_name: Ravinet, Mark last_name: Ravinet - first_name: Anja M full_name: Westram, Anja M id: 3C147470-F248-11E8-B48F-1D18A9856A87 last_name: Westram orcid: 0000-0003-1050-4969 - first_name: Kerstin full_name: Jonannesson, Kerstin last_name: Jonannesson - first_name: Roger full_name: Butlin, Roger last_name: Butlin 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' 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.' 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.' 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.' 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.' short: E. Koch, M. Ravinet, A.M. Westram, K. Jonannesson, R. Butlin, (2022). date_created: 2023-05-23T16:33:12Z date_published: 2022-07-28T00:00:00Z date_updated: 2023-08-04T09:42:10Z day: '28' ddc: - '570' department: - _id: NiBa doi: 10.5061/DRYAD.M905QFV4B main_file_link: - open_access: '1' url: https://doi.org/10.5061/dryad.m905qfv4b month: '07' oa: 1 oa_version: Published Version publisher: Dryad related_material: record: - id: '12247' relation: used_in_publication status: public status: public title: 'Data from: Genetic architecture of repeated phenotypic divergence in Littorina saxatilis ecotype evolution' tmp: image: /images/cc_0.png legal_code_url: https://creativecommons.org/publicdomain/zero/1.0/legalcode name: Creative Commons Public Domain Dedication (CC0 1.0) short: CC0 (1.0) type: research_data_reference user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 year: '2022' ... --- _id: '13076' 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." article_processing_charge: No author: - first_name: Anastasiia full_name: Postnikova, Anastasiia last_name: Postnikova - first_name: Nikita full_name: Koval, Nikita id: 2F4DB10C-F248-11E8-B48F-1D18A9856A87 last_name: Koval - first_name: Giorgi full_name: Nadiradze, Giorgi id: 3279A00C-F248-11E8-B48F-1D18A9856A87 last_name: Nadiradze - first_name: Dan-Adrian full_name: Alistarh, Dan-Adrian id: 4A899BFC-F248-11E8-B48F-1D18A9856A87 last_name: Alistarh orcid: 0000-0003-3650-940X citation: 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 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. ieee: A. Postnikova, N. Koval, G. Nadiradze, and D.-A. Alistarh, “Multi-queues can be state-of-the-art priority schedulers.” Zenodo, 2022. 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. 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). date_created: 2023-05-23T17:05:40Z date_published: 2022-01-03T00:00:00Z date_updated: 2023-08-03T06:48:34Z day: '03' ddc: - '510' department: - _id: DaAl doi: 10.5281/ZENODO.5733408 main_file_link: - open_access: '1' url: https://doi.org/10.5281/zenodo.5813846 month: '01' oa: 1 oa_version: Published Version publisher: Zenodo related_material: link: - relation: software url: https://github.com/npostnikova/mq-based-schedulers/tree/v1.1 record: - id: '11180' relation: used_in_publication status: public status: public title: Multi-queues can be state-of-the-art priority schedulers type: research_data_reference user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 year: '2022' ... --- _id: '13239' 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. 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." article_processing_charge: No author: - first_name: Thijs L. full_name: Van Der Plas, Thijs L. last_name: Van Der Plas - first_name: Tim P full_name: Vogels, Tim P id: CB6FF8D2-008F-11EA-8E08-2637E6697425 last_name: Vogels orcid: 0000-0003-3295-6181 - first_name: Sanjay G. full_name: Manohar, Sanjay G. last_name: Manohar citation: 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. 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. 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. 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. 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. 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. date_created: 2023-07-16T22:01:12Z date_published: 2022-12-01T00:00:00Z date_updated: 2023-07-18T06:36:28Z day: '01' ddc: - '000' department: - _id: TiVo ec_funded: 1 file: - access_level: open_access checksum: 7530a93ef42e10b4db1e5e4b69796e93 content_type: application/pdf creator: dernst date_created: 2023-07-18T06:32:38Z date_updated: 2023-07-18T06:32:38Z file_id: '13243' file_name: 2022_PMLR_vanderPlas.pdf file_size: 585135 relation: main_file success: 1 file_date_updated: 2023-07-18T06:32:38Z has_accepted_license: '1' intvolume: ' 199' language: - iso: eng month: '12' oa: 1 oa_version: Published Version page: 518-531 project: - _id: 0aacfa84-070f-11eb-9043-d7eb2c709234 call_identifier: H2020 grant_number: '819603' name: Learning the shape of synaptic plasticity rules for neuronal architectures and function through machine learning. publication: Proceedings of Machine Learning Research publication_identifier: eissn: - 2640-3498 publication_status: published publisher: ML Research Press quality_controlled: '1' scopus_import: '1' status: public title: Predictive learning enables neural networks to learn complex working memory tasks type: conference user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 199 year: '2022' ... --- _id: '13240' abstract: - lang: eng 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. 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." article_number: '1029114' article_processing_charge: Yes article_type: original author: - first_name: Kishor D. full_name: Ingole, Kishor D. last_name: Ingole - first_name: Nithya full_name: Nagarajan, Nithya last_name: Nagarajan - first_name: Simon full_name: Uhse, Simon last_name: Uhse - first_name: Caterina full_name: Giannini, Caterina id: e3fdddd5-f6e0-11ea-865d-ca99ee6367f4 last_name: Giannini - first_name: Armin full_name: Djamei, Armin last_name: Djamei citation: 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 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 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. 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. 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. 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. short: K.D. Ingole, N. Nagarajan, S. Uhse, C. Giannini, A. Djamei, Frontiers in Fungal Biology 3 (2022). date_created: 2023-07-16T22:01:12Z date_published: 2022-10-19T00:00:00Z date_updated: 2024-03-06T14:01:57Z day: '19' ddc: - '579' department: - _id: JiFr doi: 10.3389/ffunb.2022.1029114 file: - access_level: open_access checksum: 2254e0119c0749d6f7237084fefcece6 content_type: application/pdf creator: dernst date_created: 2023-07-17T11:46:34Z date_updated: 2023-07-17T11:46:34Z file_id: '13242' file_name: 2023_FrontiersFungalBio_Ingole.pdf file_size: 27966699 relation: main_file success: 1 file_date_updated: 2023-07-17T11:46:34Z has_accepted_license: '1' intvolume: ' 3' language: - iso: eng month: '10' oa: 1 oa_version: Published Version publication: Frontiers in Fungal Biology publication_identifier: eissn: - 2673-6128 publication_status: published publisher: Frontiers Media quality_controlled: '1' scopus_import: '1' status: public title: Tetracycline-controlled (TetON) gene expression system for the smut fungus Ustilago maydis tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87 volume: 3 year: '2022' ... --- _id: '13241' abstract: - lang: eng 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. 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." article_processing_charge: No arxiv: 1 author: - first_name: Nikola H full_name: Konstantinov, Nikola H id: 4B9D76E4-F248-11E8-B48F-1D18A9856A87 last_name: Konstantinov - first_name: Christoph full_name: Lampert, Christoph id: 40C20FD2-F248-11E8-B48F-1D18A9856A87 last_name: Lampert orcid: 0000-0001-8622-7887 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. 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. 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. 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. 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. short: N.H. Konstantinov, C. Lampert, in:, Proceedings of Machine Learning Research, ML Research Press, 2022, pp. 59–83. date_created: 2023-07-16T22:01:13Z date_published: 2022-12-01T00:00:00Z date_updated: 2023-09-26T10:44:37Z day: '01' department: - _id: ChLa external_id: arxiv: - '2102.06004' intvolume: ' 171' language: - iso: eng main_file_link: - open_access: '1' url: https://arxiv.org/abs/2102.06004 month: '12' oa: 1 oa_version: Preprint page: 59-83 publication: Proceedings of Machine Learning Research publication_identifier: eissn: - 2640-3498 publication_status: published publisher: ML Research Press quality_controlled: '1' related_material: record: - id: '10802' relation: extended_version status: public scopus_import: '1' status: public title: On the impossibility of fairness-aware learning from corrupted data type: conference user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 171 year: '2022' ... --- _id: '9199' 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." 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. article_processing_charge: No article_type: original arxiv: 1 author: - first_name: Timothy D full_name: Browning, Timothy D id: 35827D50-F248-11E8-B48F-1D18A9856A87 last_name: Browning orcid: 0000-0002-8314-0177 - first_name: Tal full_name: Horesh, Tal id: C8B7BF48-8D81-11E9-BCA9-F536E6697425 last_name: Horesh - first_name: Florian Alexander full_name: Wilsch, Florian Alexander id: 560601DA-8D36-11E9-A136-7AC1E5697425 last_name: Wilsch orcid: 0000-0001-7302-8256 citation: 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 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 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. ista: Browning TD, Horesh T, Wilsch FA. 2022. Equidistribution and freeness on Grassmannians. Algebra & Number Theory. 16(10), 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. short: T.D. Browning, T. Horesh, F.A. Wilsch, Algebra & Number Theory 16 (2022) 2385–2407. date_created: 2021-02-25T09:56:57Z date_published: 2022-12-01T00:00:00Z date_updated: 2023-08-02T06:46:38Z day: '01' department: - _id: TiBr doi: 10.2140/ant.2022.16.2385 external_id: arxiv: - '2102.11552' isi: - '000961514100004' intvolume: ' 16' isi: 1 issue: '10' language: - iso: eng main_file_link: - open_access: '1' url: https://arxiv.org/abs/2102.11552 month: '12' oa: 1 oa_version: Preprint page: 2385-2407 project: - _id: 26A8D266-B435-11E9-9278-68D0E5697425 grant_number: EP-P026710-2 name: Between rational and integral points - _id: 26AEDAB2-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: P32428 name: New frontiers of the Manin conjecture publication: Algebra & Number Theory publication_identifier: eissn: - 1944-7833 issn: - 1937-0652 publication_status: published publisher: Mathematical Sciences Publishers quality_controlled: '1' scopus_import: '1' status: public title: Equidistribution and freeness on Grassmannians type: journal_article user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8 volume: 16 year: '2022' ... --- _id: '9311' 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. ' 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" article_processing_charge: No article_type: original arxiv: 1 author: - first_name: Krishnendu full_name: Chatterjee, Krishnendu id: 2E5DCA20-F248-11E8-B48F-1D18A9856A87 last_name: Chatterjee orcid: 0000-0002-4561-241X - first_name: Raimundo J full_name: Saona Urmeneta, Raimundo J id: BD1DF4C4-D767-11E9-B658-BC13E6697425 last_name: Saona Urmeneta orcid: 0000-0001-5103-038X - first_name: Bruno full_name: Ziliotto, Bruno last_name: Ziliotto citation: 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 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 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. 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. 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. 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. date_created: 2021-04-08T09:33:31Z date_published: 2022-02-01T00:00:00Z date_updated: 2023-09-05T13:16:11Z day: '01' department: - _id: GradSch - _id: KrCh doi: 10.1287/moor.2020.1116 external_id: arxiv: - '1904.13360' isi: - '000731918100001' intvolume: ' 47' isi: 1 issue: '1' keyword: - Management Science and Operations Research - General Mathematics - Computer Science Applications language: - iso: eng main_file_link: - open_access: '1' url: https://arxiv.org/abs/1904.13360 month: '02' oa: 1 oa_version: Preprint page: 100-119 project: - _id: 25863FF4-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: S11407 name: Game Theory publication: Mathematics of Operations Research publication_identifier: eissn: - 1526-5471 issn: - 0364-765X publication_status: published publisher: Institute for Operations Research and the Management Sciences quality_controlled: '1' scopus_import: '1' status: public title: Finite-memory strategies in POMDPs with long-run average objectives type: journal_article user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1 volume: 47 year: '2022' ... --- _id: '9364' 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).' 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. article_processing_charge: Yes (via OA deal) article_type: original arxiv: 1 author: - first_name: Dante full_name: Bonolis, Dante id: 6A459894-5FDD-11E9-AF35-BB24E6697425 last_name: Bonolis 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 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. 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. 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. 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. short: D. Bonolis, Mathematical Proceedings of the Cambridge Philosophical Society 172 (2022) 563–590. date_created: 2021-05-02T22:01:29Z date_published: 2022-05-01T00:00:00Z date_updated: 2023-08-02T06:47:48Z day: '01' ddc: - '510' department: - _id: TiBr doi: 10.1017/S030500412100030X external_id: arxiv: - '1811.10563' isi: - '000784421500001' file: - access_level: open_access checksum: 614d2e9b83a78100408e4ee7752a80a8 content_type: application/pdf creator: cchlebak date_created: 2021-12-01T14:01:54Z date_updated: 2021-12-01T14:01:54Z file_id: '10395' file_name: 2021_MathProcCamPhilSoc_Bonolis.pdf file_size: 334064 relation: main_file success: 1 file_date_updated: 2021-12-01T14:01:54Z has_accepted_license: '1' intvolume: ' 172' isi: 1 issue: '3' language: - iso: eng month: '05' oa: 1 oa_version: Published Version page: 563 - 590 publication: Mathematical Proceedings of the Cambridge Philosophical Society publication_identifier: eissn: - 1469-8064 issn: - 0305-0041 publication_status: published publisher: Cambridge University Press quality_controlled: '1' scopus_import: '1' status: public title: On the size of the maximum of incomplete Kloosterman sums tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8 volume: 172 year: '2022' ... --- _id: '7577' 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. 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). article_processing_charge: No article_type: original arxiv: 1 author: - first_name: Yekini full_name: Shehu, Yekini id: 3FC7CB58-F248-11E8-B48F-1D18A9856A87 last_name: Shehu orcid: 0000-0001-9224-7139 - first_name: Olaniyi S. full_name: Iyiola, Olaniyi S. last_name: Iyiola citation: 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 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 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. ista: Shehu Y, Iyiola OS. 2022. Weak convergence for variational inequalities with inertial-type method. Applicable Analysis. 101(1), 192–216. 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. date_created: 2020-03-09T07:06:52Z date_published: 2022-01-01T00:00:00Z date_updated: 2024-03-05T14:01:52Z day: '01' ddc: - '510' - '515' - '518' department: - _id: VlKo doi: 10.1080/00036811.2020.1736287 ec_funded: 1 external_id: arxiv: - '2101.08057' isi: - '000518364100001' file: - access_level: open_access checksum: 869efe8cb09505dfa6012f67d20db63d content_type: application/pdf creator: dernst date_created: 2020-10-12T10:42:54Z date_updated: 2021-03-16T23:30:06Z embargo: 2021-03-15 file_id: '8648' file_name: 2020_ApplicAnalysis_Shehu.pdf file_size: 4282586 relation: main_file file_date_updated: 2021-03-16T23:30:06Z has_accepted_license: '1' intvolume: ' 101' isi: 1 issue: '1' language: - iso: eng month: '01' oa: 1 oa_version: Submitted Version page: 192-216 project: - _id: 25FBA906-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '616160' name: 'Discrete Optimization in Computer Vision: Theory and Practice' publication: Applicable Analysis publication_identifier: eissn: - 1563-504X issn: - 0003-6811 publication_status: published publisher: Taylor & Francis quality_controlled: '1' scopus_import: '1' status: public title: Weak convergence for variational inequalities with inertial-type method type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 101 year: '2022' ... --- _id: '7791' 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. 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. article_processing_charge: Yes (via OA deal) article_type: original arxiv: 1 author: - first_name: Arseniy full_name: Akopyan, Arseniy id: 430D2C90-F248-11E8-B48F-1D18A9856A87 last_name: Akopyan orcid: 0000-0002-2548-617X - first_name: Roman full_name: Karasev, Roman last_name: Karasev citation: 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 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. 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. ista: Akopyan A, Karasev R. 2022. When different norms lead to same billiard trajectories? European Journal of Mathematics. 8(4), 1309–1312. 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. date_created: 2020-05-03T22:00:48Z date_published: 2022-12-01T00:00:00Z date_updated: 2024-02-22T15:58:42Z day: '01' ddc: - '510' department: - _id: HeEd doi: 10.1007/s40879-020-00405-0 ec_funded: 1 external_id: arxiv: - '1912.12685' file: - access_level: open_access checksum: f53e71fd03744075adcd0b8fc1b8423d content_type: application/pdf creator: dernst date_created: 2020-05-04T10:33:42Z date_updated: 2020-07-14T12:48:03Z file_id: '7796' file_name: 2020_EuropMathematics_Akopyan.pdf file_size: 263926 relation: main_file file_date_updated: 2020-07-14T12:48:03Z has_accepted_license: '1' intvolume: ' 8' issue: '4' language: - iso: eng month: '12' oa: 1 oa_version: Published Version page: 1309 - 1312 project: - _id: 266A2E9E-B435-11E9-9278-68D0E5697425 call_identifier: H2020 grant_number: '788183' name: Alpha Shape Theory Extended - _id: B67AFEDC-15C9-11EA-A837-991A96BB2854 name: IST Austria Open Access Fund publication: European Journal of Mathematics publication_identifier: eissn: - 2199-6768 issn: - 2199-675X publication_status: published publisher: Springer Nature quality_controlled: '1' scopus_import: '1' status: public title: When different norms lead to same billiard trajectories? tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87 volume: 8 year: '2022' ... --- _id: '8125' 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 author: - first_name: William F. full_name: Podlaski, William F. last_name: Podlaski orcid: 0000-0001-6619-7502 - first_name: Everton J. full_name: Agnes, Everton J. last_name: Agnes orcid: 0000-0001-7184-7311 - first_name: Tim P full_name: Vogels, Tim P id: CB6FF8D2-008F-11EA-8E08-2637E6697425 last_name: Vogels orcid: 0000-0003-3295-6181 citation: 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 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 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. 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. 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. 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). date_created: 2020-07-16T12:24:28Z date_published: 2022-12-21T00:00:00Z date_updated: 2024-03-06T12:03:59Z day: '21' department: - _id: TiVo doi: 10.1101/2020.01.08.898528 language: - iso: eng locked: '1' main_file_link: - open_access: '1' url: 'https://doi.org/10.1101/2020.01.08.898528 ' month: '12' oa: 1 oa_version: Preprint publication: bioRxiv publication_status: published publisher: Cold Spring Harbor Laboratory status: public title: High capacity and dynamic accessibility in associative memory networks with context-dependent neuronal and synaptic gating type: preprint user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 year: '2022' ... --- _id: '14216' 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_number: '2210.01738' article_processing_charge: No arxiv: 1 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 full_name: Moschella, Luca last_name: Moschella - first_name: Emanuele full_name: Rodolà, Emanuele last_name: Rodolà - first_name: Francesco full_name: Locatello, Francesco id: 26cfd52f-2483-11ee-8040-88983bcc06d4 last_name: Locatello orcid: 0000-0002-4850-0683 citation: 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' 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.' 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. .' 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.' mla: 'Norelli, Antonio, et al. “ASIF: Coupled Data Turns Unimodal Models to Multimodal without Training.” ArXiv, 2210.01738, doi:10.48550/arXiv.2210.01738.' short: A. Norelli, M. Fumero, V. Maiorca, L. Moschella, E. Rodolà, F. Locatello, ArXiv (n.d.). date_created: 2023-08-22T14:22:04Z date_published: 2022-10-04T00:00:00Z date_updated: 2024-02-12T09:57:14Z day: '04' department: - _id: FrLo doi: 10.48550/arXiv.2210.01738 external_id: arxiv: - '2210.01738' language: - iso: eng main_file_link: - open_access: '1' url: https://doi.org/10.48550/arXiv.2210.01738 month: '10' oa: 1 oa_version: Preprint publication: arXiv publication_status: submitted status: public title: 'ASIF: Coupled data turns unimodal models to multimodal without training' type: preprint user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 year: '2022' ... --- _id: '14381' 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 article_type: original author: - first_name: Uli full_name: Wagner, Uli id: 36690CA2-F248-11E8-B48F-1D18A9856A87 last_name: Wagner orcid: 0000-0002-1494-0568 citation: 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 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. 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. ista: Wagner U. 2022. High-dimensional expanders (after Gromov, Kaufman, Kazhdan, Lubotzky, and others). Bulletin de la Societe Mathematique de France. 438, 281–294. 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. date_created: 2023-10-01T22:01:14Z date_published: 2022-01-01T00:00:00Z date_updated: 2023-10-03T08:04:03Z day: '01' department: - _id: UlWa doi: 10.24033/ast.1188 intvolume: ' 438' language: - iso: eng month: '01' oa_version: None page: 281-294 publication: Bulletin de la Societe Mathematique de France publication_identifier: eissn: - 2102-622X issn: - 0037-9484 publication_status: published publisher: Societe Mathematique de France quality_controlled: '1' scopus_import: '1' status: public title: High-dimensional expanders (after Gromov, Kaufman, Kazhdan, Lubotzky, and others) type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 438 year: '2022' ... --- _id: '14437' 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. article_processing_charge: No article_type: letter_note author: - first_name: Hendrik full_name: Utzat, Hendrik last_name: Utzat - first_name: Maria full_name: Ibáñez, Maria id: 43C61214-F248-11E8-B48F-1D18A9856A87 last_name: Ibáñez orcid: 0000-0001-5013-2843 citation: ama: Utzat H, Ibáñez M. Molecular engineering enables bright blue LEDs. Nature. 2022;612(7941):638-639. doi:10.1038/d41586-022-04447-0 apa: Utzat, H., & Ibáñez, M. (2022). Molecular engineering enables bright blue LEDs. Nature. Springer Nature. https://doi.org/10.1038/d41586-022-04447-0 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. ista: Utzat H, Ibáñez M. 2022. Molecular engineering enables bright blue LEDs. Nature. 612(7941), 638–639. 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. date_created: 2023-10-17T11:14:43Z date_published: 2022-12-21T00:00:00Z date_updated: 2023-10-18T06:26:30Z day: '21' department: - _id: MaIb doi: 10.1038/d41586-022-04447-0 external_id: pmid: - '36543947' intvolume: ' 612' issue: '7941' keyword: - Multidisciplinary language: - iso: eng month: '12' oa_version: None page: 638-639 pmid: 1 publication: Nature publication_identifier: eissn: - 1476-4687 issn: - 0028-0836 publication_status: published publisher: Springer Nature quality_controlled: '1' status: public title: Molecular engineering enables bright blue LEDs type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 612 year: '2022' ... --- _id: '14520' abstract: - lang: eng 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.' article_processing_charge: No author: - first_name: Martin full_name: Zemlicka, Martin id: 2DCF8DE6-F248-11E8-B48F-1D18A9856A87 last_name: Zemlicka - first_name: Elena full_name: Redchenko, Elena id: 2C21D6E8-F248-11E8-B48F-1D18A9856A87 last_name: Redchenko - first_name: Matilda full_name: Peruzzo, Matilda id: 3F920B30-F248-11E8-B48F-1D18A9856A87 last_name: Peruzzo orcid: 0000-0002-3415-4628 - first_name: Farid full_name: Hassani, Farid id: 2AED110C-F248-11E8-B48F-1D18A9856A87 last_name: Hassani orcid: 0000-0001-6937-5773 - first_name: Andrea full_name: Trioni, Andrea id: 42F71B44-F248-11E8-B48F-1D18A9856A87 last_name: Trioni - first_name: Shabir full_name: Barzanjeh, Shabir id: 2D25E1F6-F248-11E8-B48F-1D18A9856A87 last_name: Barzanjeh orcid: 0000-0003-0415-1423 - first_name: Johannes M full_name: Fink, Johannes M id: 4B591CBA-F248-11E8-B48F-1D18A9856A87 last_name: Fink orcid: 0000-0001-8112-028X citation: 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' 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' 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.' 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.' 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.' short: M. Zemlicka, E. Redchenko, M. Peruzzo, F. Hassani, A. Trioni, S. Barzanjeh, J.M. Fink, (2022). date_created: 2023-11-13T08:09:10Z date_published: 2022-06-28T00:00:00Z date_updated: 2024-09-10T12:23:57Z day: '28' ddc: - '530' department: - _id: JoFi doi: 10.5281/ZENODO.8408897 has_accepted_license: '1' main_file_link: - open_access: '1' url: https://doi.org/10.5281/ZENODO.8408897 month: '06' oa: 1 oa_version: Published Version publisher: Zenodo related_material: record: - id: '14517' relation: used_in_publication status: public status: public title: 'Compact vacuum gap transmon qubits: Selective and sensitive probes for superconductor surface losses' tmp: image: /images/cc_0.png legal_code_url: https://creativecommons.org/publicdomain/zero/1.0/legalcode name: Creative Commons Public Domain Dedication (CC0 1.0) short: CC0 (1.0) type: research_data_reference user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 year: '2022' ... --- _id: '14597' abstract: - lang: eng 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." article_processing_charge: No arxiv: 1 author: - first_name: Julian L full_name: Fischer, Julian L id: 2C12A0B0-F248-11E8-B48F-1D18A9856A87 last_name: Fischer orcid: 0000-0002-0479-558X - first_name: Alice full_name: Marveggio, Alice id: 25647992-AA84-11E9-9D75-8427E6697425 last_name: Marveggio citation: 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 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. ieee: J. L. Fischer and A. Marveggio, “Quantitative convergence of the vectorial Allen-Cahn equation towards multiphase mean curvature flow,” arXiv. . ista: Fischer JL, Marveggio A. Quantitative convergence of the vectorial Allen-Cahn equation towards multiphase mean curvature flow. arXiv, 10.48550/ARXIV.2203.17143. 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.). date_created: 2023-11-23T09:30:02Z date_published: 2022-03-31T00:00:00Z date_updated: 2023-11-30T13:25:02Z day: '31' department: - _id: JuFi doi: 10.48550/ARXIV.2203.17143 ec_funded: 1 external_id: arxiv: - '2203.17143' language: - iso: eng main_file_link: - open_access: '1' url: https://arxiv.org/abs/2203.17143 month: '03' oa: 1 oa_version: Preprint project: - _id: 0aa76401-070f-11eb-9043-b5bb049fa26d call_identifier: H2020 grant_number: '948819' name: Bridging Scales in Random Materials publication: arXiv publication_status: submitted related_material: record: - id: '14587' relation: dissertation_contains status: public status: public title: Quantitative convergence of the vectorial Allen-Cahn equation towards multiphase mean curvature flow type: preprint user_id: 8b945eb4-e2f2-11eb-945a-df72226e66a9 year: '2022' ... --- _id: '14600' abstract: - lang: eng 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. article_processing_charge: No arxiv: 1 author: - first_name: Dorde full_name: Zikelic, Dorde id: 294AA7A6-F248-11E8-B48F-1D18A9856A87 last_name: Zikelic orcid: 0000-0002-4681-1699 - first_name: Mathias full_name: Lechner, Mathias id: 3DC22916-F248-11E8-B48F-1D18A9856A87 last_name: Lechner - first_name: Thomas A full_name: Henzinger, Thomas A id: 40876CD8-F248-11E8-B48F-1D18A9856A87 last_name: Henzinger orcid: 0000-0002-2985-7724 - first_name: Krishnendu full_name: Chatterjee, Krishnendu id: 2E5DCA20-F248-11E8-B48F-1D18A9856A87 last_name: Chatterjee orcid: 0000-0002-4561-241X citation: 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 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. ieee: D. Zikelic, M. Lechner, T. A. Henzinger, and K. Chatterjee, “Learning control policies for stochastic systems with reach-avoid guarantees,” arXiv. . 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. 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.). date_created: 2023-11-24T13:10:09Z date_published: 2022-11-29T00:00:00Z date_updated: 2025-07-14T09:10:02Z day: '29' department: - _id: KrCh - _id: ToHe doi: 10.48550/ARXIV.2210.05308 ec_funded: 1 external_id: arxiv: - '2210.05308' language: - iso: eng license: https://creativecommons.org/licenses/by-sa/4.0/ main_file_link: - open_access: '1' url: https://arxiv.org/abs/2210.05308 month: '11' oa: 1 oa_version: Preprint project: - _id: 0599E47C-7A3F-11EA-A408-12923DDC885E call_identifier: H2020 grant_number: '863818' name: 'Formal Methods for Stochastic Models: Algorithms and Applications' - _id: 62781420-2b32-11ec-9570-8d9b63373d4d call_identifier: H2020 grant_number: '101020093' name: Vigilant Algorithmic Monitoring of Software - _id: 2564DBCA-B435-11E9-9278-68D0E5697425 call_identifier: H2020 grant_number: '665385' name: International IST Doctoral Program publication: arXiv publication_status: submitted related_material: record: - id: '14539' relation: dissertation_contains status: public - id: '14830' relation: later_version status: public status: public title: Learning control policies for stochastic systems with reach-avoid guarantees tmp: image: /images/cc_by_sa.png legal_code_url: https://creativecommons.org/licenses/by-sa/4.0/legalcode name: Creative Commons Attribution-ShareAlike 4.0 International Public License (CC BY-SA 4.0) short: CC BY-SA (4.0) type: preprint user_id: 8b945eb4-e2f2-11eb-945a-df72226e66a9 year: '2022' ... --- _id: '14601' abstract: - lang: eng 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." article_processing_charge: No arxiv: 1 author: - first_name: Dorde full_name: Zikelic, Dorde id: 294AA7A6-F248-11E8-B48F-1D18A9856A87 last_name: Zikelic orcid: 0000-0002-4681-1699 - first_name: Mathias full_name: Lechner, Mathias id: 3DC22916-F248-11E8-B48F-1D18A9856A87 last_name: Lechner - first_name: Krishnendu full_name: Chatterjee, Krishnendu id: 2E5DCA20-F248-11E8-B48F-1D18A9856A87 last_name: Chatterjee orcid: 0000-0002-4561-241X - first_name: Thomas A full_name: Henzinger, Thomas A id: 40876CD8-F248-11E8-B48F-1D18A9856A87 last_name: Henzinger orcid: 0000-0002-2985-7724 citation: ama: Zikelic D, Lechner M, Chatterjee K, Henzinger TA. Learning stabilizing policies in stochastic control systems. arXiv. doi:10.48550/arXiv.2205.11991 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 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. . ista: Zikelic D, Lechner M, Chatterjee K, Henzinger TA. Learning stabilizing policies in stochastic control systems. arXiv, 10.48550/arXiv.2205.11991. mla: Zikelic, Dorde, et al. “Learning Stabilizing Policies in Stochastic Control Systems.” ArXiv, doi:10.48550/arXiv.2205.11991. short: D. Zikelic, M. Lechner, K. Chatterjee, T.A. Henzinger, ArXiv (n.d.). date_created: 2023-11-24T13:22:30Z date_published: 2022-05-24T00:00:00Z date_updated: 2025-07-14T09:10:00Z day: '24' department: - _id: KrCh - _id: ToHe doi: 10.48550/arXiv.2205.11991 ec_funded: 1 external_id: arxiv: - '2205.11991' language: - iso: eng main_file_link: - open_access: '1' url: https://arxiv.org/abs/2205.11991 month: '05' oa: 1 oa_version: Preprint project: - _id: 62781420-2b32-11ec-9570-8d9b63373d4d call_identifier: H2020 grant_number: '101020093' name: Vigilant Algorithmic Monitoring of Software - _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 publication: arXiv publication_status: submitted related_material: record: - id: '14539' relation: dissertation_contains status: public status: public title: Learning stabilizing policies in stochastic control systems type: preprint user_id: 8b945eb4-e2f2-11eb-945a-df72226e66a9 year: '2022' ...