[{"quality_controlled":"1","article_processing_charge":"No","oa_version":"Preprint","publication_status":"published","abstract":[{"text":"Since out-of-distribution generalization is a generally ill-posed problem, various proxy targets (e.g., calibration, adversarial robustness, algorithmic corruptions, invariance across shifts) were studied across different research programs resulting in different recommendations. While sharing the same aspirational goal, these approaches have never been tested under the same\r\nexperimental conditions on real data. In this paper, we take a unified view of previous work, highlighting message discrepancies that we address empirically, and providing recommendations on how to measure the robustness of a model and how to improve it. To this end, we collect 172 publicly available dataset pairs for training and out-of-distribution evaluation of accuracy, calibration error, adversarial attacks, environment invariance, and synthetic corruptions. We fine-tune over 31k networks, from nine different architectures in the many- and\r\nfew-shot setting. Our findings confirm that in- and out-of-distribution accuracies tend to increase jointly, but show that their relation is largely dataset-dependent, and in general more nuanced and more complex than posited by previous, smaller scale studies.","lang":"eng"}],"date_created":"2023-08-22T14:01:13Z","_id":"14173","year":"2022","title":"Assaying out-of-distribution generalization in transfer learning","external_id":{"arxiv":["2207.09239"]},"day":"15","oa":1,"publication_identifier":{"isbn":["9781713871088"]},"publication":"36th Conference on Neural Information Processing Systems","citation":{"short":"F. Wenzel, A. Dittadi, P.V. Gehler, C.-J.S.-G. Carl-Johann Simon-Gabriel, M. Horn, D. Zietlow, D. Kernert, C. Russell, T. Brox, B. Schiele, B. Schölkopf, F. Locatello, in:, 36th Conference on Neural Information Processing Systems, Neural Information Processing Systems Foundation, 2022, pp. 7181–7198.","apa":"Wenzel, F., Dittadi, A., Gehler, P. V., Carl-Johann Simon-Gabriel, C.-J. S.-G., Horn, M., Zietlow, D., … Locatello, F. (2022). Assaying out-of-distribution generalization in transfer learning. In 36th Conference on Neural Information Processing Systems (Vol. 35, pp. 7181–7198). New Orleans, LA, United States: Neural Information Processing Systems Foundation.","ama":"Wenzel F, Dittadi A, Gehler PV, et al. Assaying out-of-distribution generalization in transfer learning. In: 36th Conference on Neural Information Processing Systems. Vol 35. Neural Information Processing Systems Foundation; 2022:7181-7198.","ieee":"F. Wenzel et al., “Assaying out-of-distribution generalization in transfer learning,” in 36th Conference on Neural Information Processing Systems, New Orleans, LA, United States, 2022, vol. 35, pp. 7181–7198.","mla":"Wenzel, Florian, et al. “Assaying Out-of-Distribution Generalization in Transfer Learning.” 36th Conference on Neural Information Processing Systems, vol. 35, Neural Information Processing Systems Foundation, 2022, pp. 7181–98.","ista":"Wenzel F, Dittadi A, Gehler PV, Carl-Johann Simon-Gabriel C-JS-G, Horn M, Zietlow D, Kernert D, Russell C, Brox T, Schiele B, Schölkopf B, Locatello F. 2022. Assaying out-of-distribution generalization in transfer learning. 36th Conference on Neural Information Processing Systems. NeurIPS: Neural Information Processing Systems, Advances in Neural Information Processing Systems, vol. 35, 7181–7198.","chicago":"Wenzel, Florian, Andrea Dittadi, Peter Vincent Gehler, Carl-Johann Simon-Gabriel Carl-Johann Simon-Gabriel, Max Horn, Dominik Zietlow, David Kernert, et al. “Assaying Out-of-Distribution Generalization in Transfer Learning.” In 36th Conference on Neural Information Processing Systems, 35:7181–98. Neural Information Processing Systems Foundation, 2022."},"author":[{"first_name":"Florian","last_name":"Wenzel","full_name":"Wenzel, Florian"},{"full_name":"Dittadi, Andrea","first_name":"Andrea","last_name":"Dittadi"},{"first_name":"Peter Vincent","last_name":"Gehler","full_name":"Gehler, Peter Vincent"},{"full_name":"Carl-Johann Simon-Gabriel, Carl-Johann Simon-Gabriel","first_name":"Carl-Johann Simon-Gabriel","last_name":"Carl-Johann Simon-Gabriel"},{"last_name":"Horn","first_name":"Max","full_name":"Horn, Max"},{"full_name":"Zietlow, Dominik","first_name":"Dominik","last_name":"Zietlow"},{"last_name":"Kernert","first_name":"David","full_name":"Kernert, David"},{"full_name":"Russell, Chris","first_name":"Chris","last_name":"Russell"},{"first_name":"Thomas","last_name":"Brox","full_name":"Brox, Thomas"},{"last_name":"Schiele","first_name":"Bernt","full_name":"Schiele, Bernt"},{"full_name":"Schölkopf, Bernhard","first_name":"Bernhard","last_name":"Schölkopf"},{"full_name":"Locatello, Francesco","id":"26cfd52f-2483-11ee-8040-88983bcc06d4","orcid":"0000-0002-4850-0683","last_name":"Locatello","first_name":"Francesco"}],"date_updated":"2023-09-06T10:34:43Z","main_file_link":[{"url":"https://arxiv.org/abs/2207.09239","open_access":"1"}],"month":"12","department":[{"_id":"FrLo"}],"publisher":"Neural Information Processing Systems Foundation","scopus_import":"1","arxiv":1,"page":"7181-7198","conference":{"end_date":"2022-12-09","start_date":"2022-11-28","name":"NeurIPS: Neural Information Processing Systems","location":"New Orleans, LA, United States"},"extern":"1","intvolume":" 35","alternative_title":["Advances in Neural Information Processing Systems"],"date_published":"2022-12-15T00:00:00Z","status":"public","language":[{"iso":"eng"}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","type":"conference","volume":35},{"day":"25","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","publication":"10th International Conference on Learning Representations","oa":1,"type":"conference","date_updated":"2023-09-11T09:48:36Z","citation":{"chicago":"Dittadi, Andrea, Frederik Träuble, Manuel Wüthrich, Felix Widmaier, Peter Gehler, Ole Winther, Francesco Locatello, Olivier Bachem, Bernhard Schölkopf, and Stefan Bauer. “The Role of Pretrained Representations for the OOD Generalization of  Reinforcement Learning Agents.” In 10th International Conference on Learning Representations, 2022.","ista":"Dittadi A, Träuble F, Wüthrich M, Widmaier F, Gehler P, Winther O, Locatello F, Bachem O, Schölkopf B, Bauer S. 2022. The role of pretrained representations for the OOD generalization of  reinforcement learning agents. 10th International Conference on Learning Representations. ICLR: International Conference on Learning Representations.","mla":"Dittadi, Andrea, et al. “The Role of Pretrained Representations for the OOD Generalization of  Reinforcement Learning Agents.” 10th International Conference on Learning Representations, 2022.","ieee":"A. Dittadi et al., “The role of pretrained representations for the OOD generalization of  reinforcement learning agents,” in 10th International Conference on Learning Representations, Virtual, 2022.","ama":"Dittadi A, Träuble F, Wüthrich M, et al. The role of pretrained representations for the OOD generalization of  reinforcement learning agents. In: 10th International Conference on Learning Representations. ; 2022.","apa":"Dittadi, A., Träuble, F., Wüthrich, M., Widmaier, F., Gehler, P., Winther, O., … Bauer, S. (2022). The role of pretrained representations for the OOD generalization of  reinforcement learning agents. In 10th International Conference on Learning Representations. Virtual.","short":"A. Dittadi, F. Träuble, M. Wüthrich, F. Widmaier, P. Gehler, O. Winther, F. Locatello, O. Bachem, B. Schölkopf, S. Bauer, in:, 10th International Conference on Learning Representations, 2022."},"author":[{"first_name":"Andrea","last_name":"Dittadi","full_name":"Dittadi, Andrea"},{"last_name":"Träuble","first_name":"Frederik","full_name":"Träuble, Frederik"},{"first_name":"Manuel","last_name":"Wüthrich","full_name":"Wüthrich, Manuel"},{"last_name":"Widmaier","first_name":"Felix","full_name":"Widmaier, Felix"},{"full_name":"Gehler, Peter","last_name":"Gehler","first_name":"Peter"},{"full_name":"Winther, Ole","last_name":"Winther","first_name":"Ole"},{"orcid":"0000-0002-4850-0683","full_name":"Locatello, Francesco","id":"26cfd52f-2483-11ee-8040-88983bcc06d4","last_name":"Locatello","first_name":"Francesco"},{"first_name":"Olivier","last_name":"Bachem","full_name":"Bachem, Olivier"},{"full_name":"Schölkopf, Bernhard","last_name":"Schölkopf","first_name":"Bernhard"},{"full_name":"Bauer, Stefan","last_name":"Bauer","first_name":"Stefan"}],"extern":"1","date_published":"2022-04-25T00:00:00Z","language":[{"iso":"eng"}],"external_id":{"arxiv":["2107.05686"]},"status":"public","title":"The role of pretrained representations for the OOD generalization of reinforcement learning agents","date_created":"2023-08-22T14:02:13Z","year":"2022","_id":"14174","arxiv":1,"conference":{"start_date":"2022-04-25","location":"Virtual","name":"ICLR: International Conference on Learning Representations","end_date":"2022-04-29"},"quality_controlled":"1","main_file_link":[{"open_access":"1","url":" https://doi.org/10.48550/arXiv.2107.05686"}],"oa_version":"Preprint","article_processing_charge":"No","department":[{"_id":"FrLo"}],"publication_status":"published","month":"04","abstract":[{"lang":"eng","text":"Building sample-efficient agents that generalize out-of-distribution (OOD) in real-world settings remains a fundamental unsolved problem on the path towards achieving higher-level cognition. One particularly promising approach is to begin with low-dimensional, pretrained representations of our world, which should facilitate efficient downstream learning and generalization. By training 240 representations and over 10,000 reinforcement learning (RL) policies on a simulated robotic setup, we evaluate to what extent different properties of\r\npretrained VAE-based representations affect the OOD generalization of downstream agents. We observe that many agents are surprisingly robust to realistic distribution shifts, including the challenging sim-to-real case. In addition, we find that the generalization performance of a simple downstream proxy task reliably predicts the generalization performance of our RL agents\r\nunder a wide range of OOD settings. Such proxy tasks can thus be used to select pretrained representations that will lead to agents that generalize."}]},{"article_processing_charge":"No","oa_version":"Preprint","main_file_link":[{"open_access":"1","url":"https://doi.org/10.48550/arXiv.2110.05304"}],"quality_controlled":"1","abstract":[{"lang":"eng","text":"Predicting the future trajectory of a moving agent can be easy when the past trajectory continues smoothly but is challenging when complex interactions with other agents are involved. Recent deep learning approaches for trajectory prediction show promising performance and partially attribute this to successful reasoning about agent-agent interactions. However, it remains unclear which features such black-box models actually learn to use for making predictions. This paper proposes a procedure that quantifies the contributions\r\nof different cues to model performance based on a variant of Shapley values. Applying this procedure to state-of-the-art trajectory prediction methods on standard benchmark datasets shows that they are, in fact, unable to reason about interactions. Instead, the past trajectory of the target is the only feature used for predicting its future. For a task with richer social\r\ninteraction patterns, on the other hand, the tested models do pick up such interactions to a certain extent, as quantified by our feature attribution method. We discuss the limits of the proposed method and its links to causality."}],"month":"04","department":[{"_id":"FrLo"}],"publication_status":"published","_id":"14175","year":"2022","date_created":"2023-08-22T14:02:34Z","conference":{"name":"ICLR: International Conference on Learning Representations","location":"Virtual","start_date":"2022-04-25","end_date":"2022-04-29"},"arxiv":1,"extern":"1","external_id":{"arxiv":["2110.05304"]},"status":"public","title":"You mostly walk alone: Analyzing feature attribution in trajectory prediction","language":[{"iso":"eng"}],"date_published":"2022-04-25T00:00:00Z","oa":1,"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","publication":"10th International Conference on Learning Representations","day":"25","type":"conference","date_updated":"2023-09-11T09:52:20Z","author":[{"full_name":"Makansi, Osama","first_name":"Osama","last_name":"Makansi"},{"full_name":"Kügelgen, Julius von","last_name":"Kügelgen","first_name":"Julius von"},{"orcid":"0000-0002-4850-0683","full_name":"Locatello, Francesco","id":"26cfd52f-2483-11ee-8040-88983bcc06d4","first_name":"Francesco","last_name":"Locatello"},{"first_name":"Peter","last_name":"Gehler","full_name":"Gehler, Peter"},{"full_name":"Janzing, Dominik","last_name":"Janzing","first_name":"Dominik"},{"last_name":"Brox","first_name":"Thomas","full_name":"Brox, Thomas"},{"full_name":"Schölkopf, Bernhard","first_name":"Bernhard","last_name":"Schölkopf"}],"citation":{"short":"O. Makansi, J. von Kügelgen, F. Locatello, P. Gehler, D. Janzing, T. Brox, B. Schölkopf, in:, 10th International Conference on Learning Representations, 2022.","ista":"Makansi O, Kügelgen J von, Locatello F, Gehler P, Janzing D, Brox T, Schölkopf B. 2022. You mostly walk alone: Analyzing feature attribution in trajectory prediction. 10th International Conference on Learning Representations. ICLR: International Conference on Learning Representations.","chicago":"Makansi, Osama, Julius von Kügelgen, Francesco Locatello, Peter Gehler, Dominik Janzing, Thomas Brox, and Bernhard Schölkopf. “You Mostly Walk Alone: Analyzing Feature Attribution in Trajectory Prediction.” In 10th International Conference on Learning Representations, 2022.","ama":"Makansi O, Kügelgen J von, Locatello F, et al. You mostly walk alone: Analyzing feature attribution in trajectory prediction. In: 10th International Conference on Learning Representations. ; 2022.","ieee":"O. Makansi et al., “You mostly walk alone: Analyzing feature attribution in trajectory prediction,” in 10th International Conference on Learning Representations, Virtual, 2022.","apa":"Makansi, O., Kügelgen, J. von, Locatello, F., Gehler, P., Janzing, D., Brox, T., & Schölkopf, B. (2022). You mostly walk alone: Analyzing feature attribution in trajectory prediction. In 10th International Conference on Learning Representations. Virtual.","mla":"Makansi, Osama, et al. “You Mostly Walk Alone: Analyzing Feature Attribution in Trajectory Prediction.” 10th International Conference on Learning Representations, 2022."}},{"type":"conference","citation":{"chicago":"Rahaman, Nasim, Martin Weiss, Frederik Träuble, Francesco Locatello, Alexandre Lacoste, Yoshua Bengio, Chris Pal, Li Erran Li, and Bernhard Schölkopf. “A General Purpose Neural Architecture for Geospatial Systems.” In 36th Conference on Neural Information Processing Systems, n.d.","ista":"Rahaman N, Weiss M, Träuble F, Locatello F, Lacoste A, Bengio Y, Pal C, Li LE, Schölkopf B. A general purpose neural architecture for geospatial systems. 36th Conference on Neural Information Processing Systems. NeurIPS: Neural Information Processing Systems.","mla":"Rahaman, Nasim, et al. “A General Purpose Neural Architecture for Geospatial Systems.” 36th Conference on Neural Information Processing Systems.","ama":"Rahaman N, Weiss M, Träuble F, et al. A general purpose neural architecture for geospatial systems. In: 36th Conference on Neural Information Processing Systems.","ieee":"N. Rahaman et al., “A general purpose neural architecture for geospatial systems,” in 36th Conference on Neural Information Processing Systems, New Orleans, LA, United States.","apa":"Rahaman, N., Weiss, M., Träuble, F., Locatello, F., Lacoste, A., Bengio, Y., … Schölkopf, B. (n.d.). A general purpose neural architecture for geospatial systems. In 36th Conference on Neural Information Processing Systems. New Orleans, LA, United States.","short":"N. Rahaman, M. Weiss, F. Träuble, F. Locatello, A. Lacoste, Y. Bengio, C. Pal, L.E. Li, B. Schölkopf, in:, 36th Conference on Neural Information Processing Systems, n.d."},"author":[{"full_name":"Rahaman, Nasim","last_name":"Rahaman","first_name":"Nasim"},{"first_name":"Martin","last_name":"Weiss","full_name":"Weiss, Martin"},{"full_name":"Träuble, Frederik","first_name":"Frederik","last_name":"Träuble"},{"last_name":"Locatello","first_name":"Francesco","id":"26cfd52f-2483-11ee-8040-88983bcc06d4","full_name":"Locatello, Francesco","orcid":"0000-0002-4850-0683"},{"last_name":"Lacoste","first_name":"Alexandre","full_name":"Lacoste, Alexandre"},{"first_name":"Yoshua","last_name":"Bengio","full_name":"Bengio, Yoshua"},{"first_name":"Chris","last_name":"Pal","full_name":"Pal, Chris"},{"last_name":"Li","first_name":"Li Erran","full_name":"Li, Li Erran"},{"first_name":"Bernhard","last_name":"Schölkopf","full_name":"Schölkopf, Bernhard"}],"date_updated":"2023-09-13T09:35:59Z","day":"04","publication":"36th Conference on Neural Information Processing Systems","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","oa":1,"date_published":"2022-11-04T00:00:00Z","language":[{"iso":"eng"}],"title":"A general purpose neural architecture for geospatial systems","status":"public","external_id":{"arxiv":["2211.02348"]},"extern":"1","arxiv":1,"conference":{"end_date":"2022-12-09","name":"NeurIPS: Neural Information Processing Systems","start_date":"2022-11-28","location":"New Orleans, LA, United States"},"date_created":"2023-08-22T14:21:47Z","year":"2022","_id":"14215","publication_status":"submitted","department":[{"_id":"FrLo"}],"month":"11","abstract":[{"text":"Geospatial Information Systems are used by researchers and Humanitarian Assistance and Disaster Response (HADR) practitioners to support a wide variety of important applications. However, collaboration between these actors is difficult due to the heterogeneous nature of geospatial data modalities (e.g., multi-spectral images of various resolutions, timeseries, weather data) and diversity of tasks (e.g., regression of human activity indicators or detecting forest fires). In this work, we present a roadmap towards the construction of a general-purpose neural architecture (GPNA) with a geospatial inductive bias, pre-trained on large amounts of unlabelled earth observation data in a self-supervised manner. We envision how such a model may facilitate cooperation between members of the community. We show preliminary results on the first step of the roadmap, where we instantiate an architecture that can process a wide variety of geospatial data modalities and demonstrate that it can achieve competitive performance with domain-specific architectures on tasks relating to the U.N.'s Sustainable Development Goals.","lang":"eng"}],"quality_controlled":"1","main_file_link":[{"url":"https://doi.org/10.48550/arXiv.2211.02348","open_access":"1"}],"oa_version":"Preprint","article_processing_charge":"No"},{"publication_status":"submitted","department":[{"_id":"FrLo"}],"month":"10","abstract":[{"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.","lang":"eng"}],"main_file_link":[{"url":"https://doi.org/10.48550/arXiv.2210.01738","open_access":"1"}],"oa_version":"Preprint","article_processing_charge":"No","arxiv":1,"date_created":"2023-08-22T14:22:04Z","year":"2022","_id":"14216","doi":"10.48550/arXiv.2210.01738","date_published":"2022-10-04T00:00:00Z","language":[{"iso":"eng"}],"status":"public","external_id":{"arxiv":["2210.01738"]},"title":"ASIF: Coupled data turns unimodal models to multimodal without training","article_number":"2210.01738","date_updated":"2024-02-12T09:57:14Z","type":"preprint","citation":{"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.","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. .","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","short":"A. Norelli, M. Fumero, V. Maiorca, L. Moschella, E. Rodolà, F. Locatello, ArXiv (n.d.)."},"author":[{"first_name":"Antonio","last_name":"Norelli","full_name":"Norelli, Antonio"},{"last_name":"Fumero","first_name":"Marco","full_name":"Fumero, Marco"},{"last_name":"Maiorca","first_name":"Valentino","full_name":"Maiorca, Valentino"},{"full_name":"Moschella, Luca","last_name":"Moschella","first_name":"Luca"},{"last_name":"Rodolà","first_name":"Emanuele","full_name":"Rodolà, Emanuele"},{"last_name":"Locatello","first_name":"Francesco","orcid":"0000-0002-4850-0683","full_name":"Locatello, Francesco","id":"26cfd52f-2483-11ee-8040-88983bcc06d4"}],"day":"04","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","publication":"arXiv","oa":1},{"arxiv":1,"year":"2022","_id":"14220","date_created":"2023-08-22T14:23:16Z","abstract":[{"lang":"eng","text":"Although reinforcement learning has seen remarkable progress over the last years, solving robust dexterous object-manipulation tasks in multi-object settings remains a challenge. In this paper, we focus on models that can learn manipulation tasks in fixed multi-object settings and extrapolate this skill zero-shot without any drop in performance when the number of objects changes. We consider the generic task of bringing a specific cube out of a set to a goal position. We find that previous approaches, which primarily leverage attention and graph neural network-based architectures, do not generalize their skills when the number of input objects changes while scaling as K2. We propose an alternative plug-and-play module based on relational inductive biases to overcome these limitations. Besides exceeding performances in their training environment, we show that our approach, which scales linearly in K, allows agents to extrapolate and generalize zero-shot to any new object number."}],"publication_status":"submitted","department":[{"_id":"FrLo"}],"month":"01","oa_version":"Preprint","article_processing_charge":"No","main_file_link":[{"url":"https://doi.org/10.48550/arXiv.2201.13388","open_access":"1"}],"citation":{"ieee":"D. Mambelli, F. Träuble, S. Bauer, B. Schölkopf, and F. Locatello, “Compositional multi-object reinforcement learning with linear relation networks,” arXiv. .","ama":"Mambelli D, Träuble F, Bauer S, Schölkopf B, Locatello F. Compositional multi-object reinforcement learning with linear relation networks. arXiv. doi:10.48550/arXiv.2201.13388","apa":"Mambelli, D., Träuble, F., Bauer, S., Schölkopf, B., & Locatello, F. (n.d.). Compositional multi-object reinforcement learning with linear relation networks. arXiv. https://doi.org/10.48550/arXiv.2201.13388","mla":"Mambelli, Davide, et al. “Compositional Multi-Object Reinforcement Learning with Linear Relation Networks.” ArXiv, 2201.13388, doi:10.48550/arXiv.2201.13388.","ista":"Mambelli D, Träuble F, Bauer S, Schölkopf B, Locatello F. Compositional multi-object reinforcement learning with linear relation networks. arXiv, 2201.13388.","chicago":"Mambelli, Davide, Frederik Träuble, Stefan Bauer, Bernhard Schölkopf, and Francesco Locatello. “Compositional Multi-Object Reinforcement Learning with Linear Relation Networks.” ArXiv, n.d. https://doi.org/10.48550/arXiv.2201.13388.","short":"D. Mambelli, F. Träuble, S. Bauer, B. Schölkopf, F. Locatello, ArXiv (n.d.)."},"type":"preprint","author":[{"full_name":"Mambelli, Davide","last_name":"Mambelli","first_name":"Davide"},{"full_name":"Träuble, Frederik","last_name":"Träuble","first_name":"Frederik"},{"full_name":"Bauer, Stefan","last_name":"Bauer","first_name":"Stefan"},{"last_name":"Schölkopf","first_name":"Bernhard","full_name":"Schölkopf, Bernhard"},{"last_name":"Locatello","first_name":"Francesco","full_name":"Locatello, Francesco","id":"26cfd52f-2483-11ee-8040-88983bcc06d4","orcid":"0000-0002-4850-0683"}],"date_updated":"2023-09-11T11:49:40Z","publication":"arXiv","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","oa":1,"day":"31","language":[{"iso":"eng"}],"external_id":{"arxiv":["2201.13388"]},"status":"public","title":"Compositional multi-object reinforcement learning with linear relation networks","doi":"10.48550/arXiv.2201.13388","date_published":"2022-01-31T00:00:00Z","article_number":"2201.13388","extern":"1"},{"abstract":[{"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.","lang":"eng"}],"month":"01","publication_status":"published","department":[{"_id":"UlWa"}],"publisher":"Societe Mathematique de France","article_type":"original","article_processing_charge":"No","oa_version":"None","quality_controlled":"1","page":"281-294","_id":"14381","scopus_import":"1","year":"2022","date_created":"2023-10-01T22:01:14Z","title":"High-dimensional expanders (after Gromov, Kaufman, Kazhdan, Lubotzky, and others)","status":"public","language":[{"iso":"eng"}],"date_published":"2022-01-01T00:00:00Z","doi":"10.24033/ast.1188","intvolume":" 438","volume":438,"citation":{"short":"U. Wagner, Bulletin de La Societe Mathematique de France 438 (2022) 281–294.","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.","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.","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","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","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."},"date_updated":"2023-10-03T08:04:03Z","author":[{"full_name":"Wagner, Uli","id":"36690CA2-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-1494-0568","first_name":"Uli","last_name":"Wagner"}],"type":"journal_article","publication":"Bulletin de la Societe Mathematique de France","publication_identifier":{"eissn":["2102-622X"],"issn":["0037-9484"]},"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","day":"01"},{"citation":{"short":"H. Utzat, M. Ibáñez, Nature 612 (2022) 638–639.","ista":"Utzat H, Ibáñez M. 2022. Molecular engineering enables bright blue LEDs. Nature. 612(7941), 638–639.","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.","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","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."},"date_updated":"2023-10-18T06:26:30Z","author":[{"first_name":"Hendrik","last_name":"Utzat","full_name":"Utzat, Hendrik"},{"first_name":"Maria","last_name":"Ibáñez","full_name":"Ibáñez, Maria","id":"43C61214-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0001-5013-2843"}],"publication_identifier":{"issn":["0028-0836"],"eissn":["1476-4687"]},"publication":"Nature","day":"21","external_id":{"pmid":["36543947"]},"title":"Molecular engineering enables bright blue LEDs","issue":"7941","_id":"14437","year":"2022","date_created":"2023-10-17T11:14:43Z","pmid":1,"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."}],"publication_status":"published","article_type":"letter_note","article_processing_charge":"No","keyword":["Multidisciplinary"],"oa_version":"None","quality_controlled":"1","volume":612,"type":"journal_article","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","status":"public","language":[{"iso":"eng"}],"date_published":"2022-12-21T00:00:00Z","doi":"10.1038/d41586-022-04447-0","intvolume":" 612","page":"638-639","month":"12","publisher":"Springer Nature","department":[{"_id":"MaIb"}]},{"has_accepted_license":"1","ddc":["530"],"date_published":"2022-06-28T00:00:00Z","doi":"10.5281/ZENODO.8408897","tmp":{"image":"/images/cc_0.png","name":"Creative Commons Public Domain Dedication (CC0 1.0)","short":"CC0 (1.0)","legal_code_url":"https://creativecommons.org/publicdomain/zero/1.0/legalcode"},"status":"public","title":"Compact vacuum gap transmon qubits: Selective and sensitive probes for superconductor surface losses","day":"28","oa":1,"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","author":[{"last_name":"Zemlicka","first_name":"Martin","full_name":"Zemlicka, Martin","id":"2DCF8DE6-F248-11E8-B48F-1D18A9856A87"},{"full_name":"Redchenko, Elena","id":"2C21D6E8-F248-11E8-B48F-1D18A9856A87","first_name":"Elena","last_name":"Redchenko"},{"full_name":"Peruzzo, Matilda","id":"3F920B30-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-3415-4628","first_name":"Matilda","last_name":"Peruzzo"},{"orcid":"0000-0001-6937-5773","full_name":"Hassani, Farid","id":"2AED110C-F248-11E8-B48F-1D18A9856A87","last_name":"Hassani","first_name":"Farid"},{"id":"42F71B44-F248-11E8-B48F-1D18A9856A87","full_name":"Trioni, Andrea","first_name":"Andrea","last_name":"Trioni"},{"first_name":"Shabir","last_name":"Barzanjeh","orcid":"0000-0003-0415-1423","id":"2D25E1F6-F248-11E8-B48F-1D18A9856A87","full_name":"Barzanjeh, Shabir"},{"full_name":"Fink, Johannes M","id":"4B591CBA-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0001-8112-028X","last_name":"Fink","first_name":"Johannes M"}],"type":"research_data_reference","date_updated":"2024-09-10T12:23:57Z","citation":{"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.","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","ieee":"M. Zemlicka et al., “Compact vacuum gap transmon qubits: Selective and sensitive probes for superconductor surface losses.” Zenodo, 2022.","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","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)."},"main_file_link":[{"open_access":"1","url":"https://doi.org/10.5281/ZENODO.8408897"}],"license":"https://creativecommons.org/publicdomain/zero/1.0/","article_processing_charge":"No","oa_version":"Published Version","month":"06","publisher":"Zenodo","department":[{"_id":"JoFi"}],"related_material":{"record":[{"relation":"used_in_publication","id":"14517","status":"public"}]},"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."}],"date_created":"2023-11-13T08:09:10Z","_id":"14520","year":"2022"},{"status":"public","external_id":{"arxiv":["2203.17143"]},"title":"Quantitative convergence of the vectorial Allen-Cahn equation towards multiphase mean curvature flow","project":[{"name":"Bridging Scales in Random Materials","grant_number":"948819","_id":"0aa76401-070f-11eb-9043-b5bb049fa26d","call_identifier":"H2020"}],"language":[{"iso":"eng"}],"date_published":"2022-03-31T00:00:00Z","doi":"10.48550/ARXIV.2203.17143","oa":1,"publication":"arXiv","user_id":"8b945eb4-e2f2-11eb-945a-df72226e66a9","day":"31","author":[{"orcid":"0000-0002-0479-558X","id":"2C12A0B0-F248-11E8-B48F-1D18A9856A87","full_name":"Fischer, Julian L","first_name":"Julian L","last_name":"Fischer"},{"first_name":"Alice","last_name":"Marveggio","id":"25647992-AA84-11E9-9D75-8427E6697425","full_name":"Marveggio, Alice"}],"type":"preprint","citation":{"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","ieee":"J. L. Fischer and A. Marveggio, “Quantitative convergence of the vectorial Allen-Cahn equation towards multiphase mean curvature flow,” arXiv. .","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","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.","ista":"Fischer JL, Marveggio A. Quantitative convergence of the vectorial Allen-Cahn equation towards multiphase mean curvature flow. arXiv, 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.","short":"J.L. Fischer, A. Marveggio, ArXiv (n.d.)."},"date_updated":"2023-11-30T13:25:02Z","article_processing_charge":"No","oa_version":"Preprint","main_file_link":[{"open_access":"1","url":"https://arxiv.org/abs/2203.17143"}],"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."}],"month":"03","publication_status":"submitted","related_material":{"record":[{"id":"14587","status":"public","relation":"dissertation_contains"}]},"department":[{"_id":"JuFi"}],"_id":"14597","year":"2022","date_created":"2023-11-23T09:30:02Z","ec_funded":1,"arxiv":1},{"doi":"10.48550/ARXIV.2210.05308","date_published":"2022-11-29T00:00:00Z","language":[{"iso":"eng"}],"project":[{"call_identifier":"H2020","grant_number":"863818","_id":"0599E47C-7A3F-11EA-A408-12923DDC885E","name":"Formal Methods for Stochastic Models: Algorithms and Applications"},{"call_identifier":"H2020","_id":"62781420-2b32-11ec-9570-8d9b63373d4d","grant_number":"101020093","name":"Vigilant Algorithmic Monitoring of Software"},{"name":"International IST Doctoral Program","grant_number":"665385","call_identifier":"H2020","_id":"2564DBCA-B435-11E9-9278-68D0E5697425"}],"title":"Learning control policies for stochastic systems with reach-avoid guarantees","tmp":{"name":"Creative Commons Attribution-ShareAlike 4.0 International Public License (CC BY-SA 4.0)","short":"CC BY-SA (4.0)","image":"/images/cc_by_sa.png","legal_code_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode"},"external_id":{"arxiv":["2210.05308"]},"status":"public","day":"29","user_id":"8b945eb4-e2f2-11eb-945a-df72226e66a9","publication":"arXiv","oa":1,"type":"preprint","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.","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.","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","ieee":"D. Zikelic, M. Lechner, T. A. Henzinger, and K. Chatterjee, “Learning control policies for stochastic systems with reach-avoid guarantees,” arXiv. .","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","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_updated":"2025-07-14T09:10:02Z","author":[{"first_name":"Dorde","last_name":"Zikelic","id":"294AA7A6-F248-11E8-B48F-1D18A9856A87","full_name":"Zikelic, Dorde","orcid":"0000-0002-4681-1699"},{"full_name":"Lechner, Mathias","id":"3DC22916-F248-11E8-B48F-1D18A9856A87","last_name":"Lechner","first_name":"Mathias"},{"full_name":"Henzinger, Thomas A","id":"40876CD8-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-2985-7724","last_name":"Henzinger","first_name":"Thomas A"},{"id":"2E5DCA20-F248-11E8-B48F-1D18A9856A87","full_name":"Chatterjee, Krishnendu","orcid":"0000-0002-4561-241X","first_name":"Krishnendu","last_name":"Chatterjee"}],"license":"https://creativecommons.org/licenses/by-sa/4.0/","main_file_link":[{"url":"https://arxiv.org/abs/2210.05308","open_access":"1"}],"oa_version":"Preprint","article_processing_charge":"No","related_material":{"record":[{"status":"public","id":"14539","relation":"dissertation_contains"},{"status":"public","id":"14830","relation":"later_version"}]},"department":[{"_id":"KrCh"},{"_id":"ToHe"}],"publication_status":"submitted","month":"11","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"}],"date_created":"2023-11-24T13:10:09Z","ec_funded":1,"year":"2022","_id":"14600","arxiv":1},{"day":"24","oa":1,"publication":"arXiv","user_id":"8b945eb4-e2f2-11eb-945a-df72226e66a9","type":"preprint","citation":{"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.","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.","ieee":"D. Zikelic, M. Lechner, K. Chatterjee, and T. A. Henzinger, “Learning stabilizing policies in stochastic control systems,” arXiv. .","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","short":"D. Zikelic, M. Lechner, K. Chatterjee, T.A. Henzinger, ArXiv (n.d.)."},"author":[{"first_name":"Dorde","last_name":"Zikelic","id":"294AA7A6-F248-11E8-B48F-1D18A9856A87","full_name":"Zikelic, Dorde","orcid":"0000-0002-4681-1699"},{"last_name":"Lechner","first_name":"Mathias","id":"3DC22916-F248-11E8-B48F-1D18A9856A87","full_name":"Lechner, Mathias"},{"orcid":"0000-0002-4561-241X","full_name":"Chatterjee, Krishnendu","id":"2E5DCA20-F248-11E8-B48F-1D18A9856A87","last_name":"Chatterjee","first_name":"Krishnendu"},{"orcid":"0000-0002-2985-7724","id":"40876CD8-F248-11E8-B48F-1D18A9856A87","full_name":"Henzinger, Thomas A","last_name":"Henzinger","first_name":"Thomas A"}],"date_updated":"2025-07-14T09:10:00Z","date_published":"2022-05-24T00:00:00Z","doi":"10.48550/arXiv.2205.11991","title":"Learning stabilizing policies in stochastic control systems","status":"public","external_id":{"arxiv":["2205.11991"]},"language":[{"iso":"eng"}],"project":[{"name":"Vigilant Algorithmic Monitoring of Software","call_identifier":"H2020","grant_number":"101020093","_id":"62781420-2b32-11ec-9570-8d9b63373d4d"},{"_id":"0599E47C-7A3F-11EA-A408-12923DDC885E","call_identifier":"H2020","grant_number":"863818","name":"Formal Methods for Stochastic Models: Algorithms and Applications"},{"name":"International IST Doctoral Program","_id":"2564DBCA-B435-11E9-9278-68D0E5697425","call_identifier":"H2020","grant_number":"665385"}],"ec_funded":1,"date_created":"2023-11-24T13:22:30Z","_id":"14601","year":"2022","arxiv":1,"main_file_link":[{"open_access":"1","url":"https://arxiv.org/abs/2205.11991"}],"article_processing_charge":"No","oa_version":"Preprint","month":"05","related_material":{"record":[{"relation":"dissertation_contains","status":"public","id":"14539"}]},"department":[{"_id":"KrCh"},{"_id":"ToHe"}],"publication_status":"submitted","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"}]},{"publication_identifier":{"eissn":["1563-504X"],"issn":["0003-6811"]},"publication":"Applicable Analysis","oa":1,"day":"01","citation":{"short":"Y. Shehu, O.S. Iyiola, Applicable Analysis 101 (2022) 192–216.","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","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.","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","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.","ista":"Shehu Y, Iyiola OS. 2022. Weak convergence for variational inequalities with inertial-type method. Applicable Analysis. 101(1), 192–216.","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."},"author":[{"first_name":"Yekini","last_name":"Shehu","orcid":"0000-0001-9224-7139","full_name":"Shehu, Yekini","id":"3FC7CB58-F248-11E8-B48F-1D18A9856A87"},{"full_name":"Iyiola, Olaniyi S.","first_name":"Olaniyi S.","last_name":"Iyiola"}],"date_updated":"2024-03-05T14:01:52Z","issue":"1","has_accepted_license":"1","project":[{"name":"Discrete Optimization in Computer Vision: Theory and Practice","call_identifier":"FP7","_id":"25FBA906-B435-11E9-9278-68D0E5697425","grant_number":"616160"}],"title":"Weak convergence for variational inequalities with inertial-type method","external_id":{"arxiv":["2101.08057"],"isi":["000518364100001"]},"year":"2022","_id":"7577","ec_funded":1,"date_created":"2020-03-09T07:06:52Z","oa_version":"Submitted Version","article_processing_charge":"No","quality_controlled":"1","file":[{"content_type":"application/pdf","file_size":4282586,"checksum":"869efe8cb09505dfa6012f67d20db63d","access_level":"open_access","creator":"dernst","file_id":"8648","date_created":"2020-10-12T10:42:54Z","relation":"main_file","file_name":"2020_ApplicAnalysis_Shehu.pdf","date_updated":"2021-03-16T23:30:06Z","embargo":"2021-03-15"}],"abstract":[{"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.","lang":"eng"}],"article_type":"original","publication_status":"published","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","file_date_updated":"2021-03-16T23:30:06Z","volume":101,"type":"journal_article","ddc":["510","515","518"],"intvolume":" 101","language":[{"iso":"eng"}],"status":"public","doi":"10.1080/00036811.2020.1736287","date_published":"2022-01-01T00:00:00Z","scopus_import":"1","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).","page":"192-216","arxiv":1,"isi":1,"department":[{"_id":"VlKo"}],"publisher":"Taylor & Francis","month":"01"},{"intvolume":" 8","ddc":["510"],"language":[{"iso":"eng"}],"tmp":{"legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png","short":"CC BY (4.0)","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)"},"status":"public","doi":"10.1007/s40879-020-00405-0","date_published":"2022-12-01T00:00:00Z","user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87","file_date_updated":"2020-07-14T12:48:03Z","volume":8,"type":"journal_article","department":[{"_id":"HeEd"}],"publisher":"Springer Nature","month":"12","scopus_import":"1","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.","page":"1309 - 1312","arxiv":1,"issue":"4","has_accepted_license":"1","project":[{"call_identifier":"H2020","grant_number":"788183","_id":"266A2E9E-B435-11E9-9278-68D0E5697425","name":"Alpha Shape Theory Extended"},{"name":"IST Austria Open Access Fund","_id":"B67AFEDC-15C9-11EA-A837-991A96BB2854"}],"title":"When different norms lead to same billiard trajectories?","external_id":{"arxiv":["1912.12685"]},"publication_identifier":{"issn":["2199-675X"],"eissn":["2199-6768"]},"publication":"European Journal of Mathematics","oa":1,"day":"01","author":[{"orcid":"0000-0002-2548-617X","full_name":"Akopyan, Arseniy","id":"430D2C90-F248-11E8-B48F-1D18A9856A87","first_name":"Arseniy","last_name":"Akopyan"},{"first_name":"Roman","last_name":"Karasev","full_name":"Karasev, Roman"}],"date_updated":"2024-02-22T15:58:42Z","citation":{"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.","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","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.","ista":"Akopyan A, Karasev R. 2022. When different norms lead to same billiard trajectories? European Journal of Mathematics. 8(4), 1309–1312.","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."},"oa_version":"Published Version","article_processing_charge":"Yes (via OA deal)","quality_controlled":"1","file":[{"relation":"main_file","date_created":"2020-05-04T10:33:42Z","file_id":"7796","file_name":"2020_EuropMathematics_Akopyan.pdf","date_updated":"2020-07-14T12:48:03Z","file_size":263926,"content_type":"application/pdf","checksum":"f53e71fd03744075adcd0b8fc1b8423d","creator":"dernst","access_level":"open_access"}],"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."}],"publication_status":"published","article_type":"original","year":"2022","_id":"7791","date_created":"2020-05-03T22:00:48Z","ec_funded":1},{"language":[{"iso":"eng"}],"status":"public","title":"High capacity and dynamic accessibility in associative memory networks with context-dependent neuronal and synaptic gating","locked":"1","doi":"10.1101/2020.01.08.898528","date_published":"2022-12-21T00:00:00Z","type":"preprint","citation":{"short":"W.F. Podlaski, E.J. Agnes, T.P. Vogels, BioRxiv (2022).","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","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.","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","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.","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.","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."},"author":[{"last_name":"Podlaski","first_name":"William F.","orcid":"0000-0001-6619-7502","full_name":"Podlaski, William F."},{"full_name":"Agnes, Everton J.","orcid":"0000-0001-7184-7311","first_name":"Everton J.","last_name":"Agnes"},{"last_name":"Vogels","first_name":"Tim P","full_name":"Vogels, Tim P","id":"CB6FF8D2-008F-11EA-8E08-2637E6697425","orcid":"0000-0003-3295-6181"}],"date_updated":"2024-03-06T12:03:59Z","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","publication":"bioRxiv","oa":1,"day":"21","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."}],"publisher":"Cold Spring Harbor Laboratory","publication_status":"published","department":[{"_id":"TiVo"}],"month":"12","oa_version":"Preprint","article_processing_charge":"No","main_file_link":[{"open_access":"1","url":"https://doi.org/10.1101/2020.01.08.898528 "}],"year":"2022","_id":"8125","date_created":"2020-07-16T12:24:28Z"},{"isi":1,"main_file_link":[{"url":"https://arxiv.org/abs/2102.11552","open_access":"1"}],"department":[{"_id":"TiBr"}],"publisher":"Mathematical Sciences Publishers","month":"12","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.","scopus_import":"1","arxiv":1,"page":"2385-2407","intvolume":" 16","doi":"10.2140/ant.2022.16.2385","date_published":"2022-12-01T00:00:00Z","language":[{"iso":"eng"}],"status":"public","user_id":"4359f0d1-fa6c-11eb-b949-802e58b17ae8","type":"journal_article","volume":16,"quality_controlled":"1","oa_version":"Preprint","article_processing_charge":"No","article_type":"original","publication_status":"published","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."}],"date_created":"2021-02-25T09:56:57Z","year":"2022","_id":"9199","issue":"10","project":[{"name":"Between rational and integral points","grant_number":"EP-P026710-2","_id":"26A8D266-B435-11E9-9278-68D0E5697425"},{"call_identifier":"FWF","_id":"26AEDAB2-B435-11E9-9278-68D0E5697425","grant_number":"P32428","name":"New frontiers of the Manin conjecture"}],"external_id":{"arxiv":["2102.11552"],"isi":["000961514100004"]},"title":"Equidistribution and freeness on Grassmannians","day":"01","publication":"Algebra & Number Theory","publication_identifier":{"issn":["1937-0652"],"eissn":["1944-7833"]},"oa":1,"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.","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.","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.","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","short":"T.D. Browning, T. Horesh, F.A. Wilsch, Algebra & Number Theory 16 (2022) 2385–2407."},"author":[{"first_name":"Timothy D","last_name":"Browning","full_name":"Browning, Timothy D","id":"35827D50-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-8314-0177"},{"full_name":"Horesh, Tal","id":"C8B7BF48-8D81-11E9-BCA9-F536E6697425","last_name":"Horesh","first_name":"Tal"},{"first_name":"Florian Alexander","last_name":"Wilsch","orcid":"0000-0001-7302-8256","id":"560601DA-8D36-11E9-A136-7AC1E5697425","full_name":"Wilsch, Florian Alexander"}],"date_updated":"2023-08-02T06:46:38Z"},{"arxiv":1,"page":"100-119","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","scopus_import":"1","month":"02","department":[{"_id":"GradSch"},{"_id":"KrCh"}],"publisher":"Institute for Operations Research and the Management Sciences","main_file_link":[{"open_access":"1","url":"https://arxiv.org/abs/1904.13360"}],"isi":1,"type":"journal_article","volume":47,"user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","date_published":"2022-02-01T00:00:00Z","doi":"10.1287/moor.2020.1116","status":"public","language":[{"iso":"eng"}],"intvolume":" 47","date_created":"2021-04-08T09:33:31Z","_id":"9311","year":"2022","article_type":"original","publication_status":"published","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. "}],"quality_controlled":"1","keyword":["Management Science and Operations Research","General Mathematics","Computer Science Applications"],"article_processing_charge":"No","oa_version":"Preprint","author":[{"first_name":"Krishnendu","last_name":"Chatterjee","orcid":"0000-0002-4561-241X","id":"2E5DCA20-F248-11E8-B48F-1D18A9856A87","full_name":"Chatterjee, Krishnendu"},{"first_name":"Raimundo J","last_name":"Saona Urmeneta","full_name":"Saona Urmeneta, Raimundo J","id":"BD1DF4C4-D767-11E9-B658-BC13E6697425","orcid":"0000-0001-5103-038X"},{"full_name":"Ziliotto, Bruno","last_name":"Ziliotto","first_name":"Bruno"}],"date_updated":"2023-09-05T13:16:11Z","citation":{"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.","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.","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.","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.","short":"K. Chatterjee, R.J. Saona Urmeneta, B. Ziliotto, Mathematics of Operations Research 47 (2022) 100–119."},"day":"01","oa":1,"publication":"Mathematics of Operations Research","publication_identifier":{"eissn":["1526-5471"],"issn":["0364-765X"]},"external_id":{"isi":["000731918100001"],"arxiv":["1904.13360"]},"title":"Finite-memory strategies in POMDPs with long-run average objectives","project":[{"grant_number":"S11407","_id":"25863FF4-B435-11E9-9278-68D0E5697425","call_identifier":"FWF","name":"Game Theory"}],"issue":"1"},{"_id":"9364","year":"2022","date_created":"2021-05-02T22:01:29Z","abstract":[{"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).","lang":"eng"}],"file":[{"date_updated":"2021-12-01T14:01:54Z","file_name":"2021_MathProcCamPhilSoc_Bonolis.pdf","file_id":"10395","success":1,"relation":"main_file","date_created":"2021-12-01T14:01:54Z","access_level":"open_access","creator":"cchlebak","checksum":"614d2e9b83a78100408e4ee7752a80a8","file_size":334064,"content_type":"application/pdf"}],"publication_status":"published","article_type":"original","article_processing_charge":"Yes (via OA deal)","oa_version":"Published Version","quality_controlled":"1","citation":{"short":"D. Bonolis, Mathematical Proceedings of the Cambridge Philosophical Society 172 (2022) 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.","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.","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.","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"},"author":[{"first_name":"Dante","last_name":"Bonolis","full_name":"Bonolis, Dante","id":"6A459894-5FDD-11E9-AF35-BB24E6697425"}],"date_updated":"2023-08-02T06:47:48Z","oa":1,"publication":"Mathematical Proceedings of the Cambridge Philosophical Society","publication_identifier":{"issn":["0305-0041"],"eissn":["1469-8064"]},"day":"01","title":"On the size of the maximum of incomplete Kloosterman sums","external_id":{"isi":["000784421500001"],"arxiv":["1811.10563"]},"issue":"3","has_accepted_license":"1","page":"563 - 590","arxiv":1,"scopus_import":"1","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","department":[{"_id":"TiBr"}],"publisher":"Cambridge University Press","isi":1,"volume":172,"type":"journal_article","user_id":"4359f0d1-fa6c-11eb-b949-802e58b17ae8","file_date_updated":"2021-12-01T14:01:54Z","status":"public","tmp":{"legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png","short":"CC BY (4.0)","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)"},"language":[{"iso":"eng"}],"date_published":"2022-05-01T00:00:00Z","doi":"10.1017/S030500412100030X","ddc":["510"],"intvolume":" 172"},{"project":[{"name":"ISTplus - Postdoctoral Fellowships","grant_number":"754411","_id":"260C2330-B435-11E9-9278-68D0E5697425","call_identifier":"H2020"}],"title":"The topological correctness of PL approximations of isomanifolds","external_id":{"isi":["000673039600001"]},"has_accepted_license":"1","author":[{"full_name":"Boissonnat, Jean-Daniel","last_name":"Boissonnat","first_name":"Jean-Daniel"},{"id":"307CFBC8-F248-11E8-B48F-1D18A9856A87","full_name":"Wintraecken, Mathijs","orcid":"0000-0002-7472-2220","last_name":"Wintraecken","first_name":"Mathijs"}],"date_updated":"2023-08-02T06:49:17Z","citation":{"short":"J.-D. Boissonnat, M. Wintraecken, Foundations of Computational Mathematics 22 (2022) 967–1012.","chicago":"Boissonnat, Jean-Daniel, and Mathijs Wintraecken. “The Topological Correctness of PL Approximations of Isomanifolds.” Foundations of Computational Mathematics . Springer Nature, 2022. https://doi.org/10.1007/s10208-021-09520-0.","ista":"Boissonnat J-D, Wintraecken M. 2022. The topological correctness of PL approximations of isomanifolds. Foundations of Computational Mathematics . 22, 967–1012.","mla":"Boissonnat, Jean-Daniel, and Mathijs Wintraecken. “The Topological Correctness of PL Approximations of Isomanifolds.” Foundations of Computational Mathematics , vol. 22, Springer Nature, 2022, pp. 967–1012, doi:10.1007/s10208-021-09520-0.","ama":"Boissonnat J-D, Wintraecken M. The topological correctness of PL approximations of isomanifolds. Foundations of Computational Mathematics . 2022;22:967-1012. doi:10.1007/s10208-021-09520-0","ieee":"J.-D. Boissonnat and M. Wintraecken, “The topological correctness of PL approximations of isomanifolds,” Foundations of Computational Mathematics , vol. 22. Springer Nature, pp. 967–1012, 2022.","apa":"Boissonnat, J.-D., & Wintraecken, M. (2022). The topological correctness of PL approximations of isomanifolds. Foundations of Computational Mathematics . Springer Nature. https://doi.org/10.1007/s10208-021-09520-0"},"day":"01","publication":"Foundations of Computational Mathematics ","publication_identifier":{"eissn":["1615-3383"]},"oa":1,"publication_status":"published","article_type":"original","related_material":{"record":[{"id":"7952","status":"public","relation":"earlier_version"}]},"file":[{"access_level":"open_access","creator":"mwintrae","file_size":1455699,"content_type":"application/pdf","checksum":"f1d372ec3c08ec22e84f8e93e1126b8c","date_updated":"2021-07-14T06:44:36Z","file_id":"9650","relation":"main_file","date_created":"2021-07-14T06:44:36Z","file_name":"Boissonnat-Wintraecken2021_Article_TheTopologicalCorrectnessOfPLA.pdf"}],"abstract":[{"text":"Isomanifolds are the generalization of isosurfaces to arbitrary dimension and codimension, i.e. manifolds defined as the zero set of some multivariate vector-valued smooth function f : Rd → Rd−n. A natural (and efficient) way to approximate an isomanifold is to consider its Piecewise-Linear (PL) approximation based on a triangulation T of the ambient space Rd. In this paper, we give conditions under which the PL-approximation of an isomanifold is topologically equivalent to the isomanifold. The conditions are easy to satisfy in the sense that they can always be met by taking a sufficiently\r\nfine triangulation T . This contrasts with previous results on the triangulation of manifolds where, in arbitrary dimensions, delicate perturbations are needed to guarantee topological correctness, which leads to strong limitations in practice. We further give a bound on the Fréchet distance between the original isomanifold and its PL-approximation. Finally we show analogous results for the PL-approximation of an isomanifold with boundary.","lang":"eng"}],"quality_controlled":"1","oa_version":"Published Version","article_processing_charge":"Yes (via OA deal)","date_created":"2021-07-14T06:44:53Z","ec_funded":1,"year":"2022","_id":"9649","doi":"10.1007/s10208-021-09520-0","date_published":"2022-01-01T00:00:00Z","language":[{"iso":"eng"}],"status":"public","tmp":{"legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png","short":"CC BY (4.0)","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)"},"intvolume":" 22","ddc":["516"],"type":"journal_article","volume":22,"file_date_updated":"2021-07-14T06:44:36Z","user_id":"4359f0d1-fa6c-11eb-b949-802e58b17ae8","publisher":"Springer Nature","department":[{"_id":"HeEd"}],"month":"0","isi":1,"page":"967-1012","acknowledgement":"First and foremost, we acknowledge Siargey Kachanovich for discussions. We thank Herbert Edelsbrunner and all members of his group, all former and current members of the Datashape team (formerly known as Geometrica), and André Lieutier for encouragement. We further thank the reviewers of Foundations of Computational Mathematics and the reviewers and program committee of the Symposium on Computational Geometry for their feedback, which improved the exposition.\r\nThis work was funded by the European Research Council under the European Union’s ERC Grant Agreement number 339025 GUDHI (Algorithmic Foundations of Geometric Understanding in Higher Dimensions). This work was also supported by the French government, through the 3IA Côte d’Azur Investments in the Future project managed by the National Research Agency (ANR) with the reference number ANR-19-P3IA-0002. Mathijs Wintraecken also received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement no. 754411.","scopus_import":"1"},{"volume":23,"type":"journal_article","user_id":"4359f0d1-fa6c-11eb-b949-802e58b17ae8","file_date_updated":"2022-07-25T07:11:32Z","status":"public","tmp":{"legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png","short":"CC BY (4.0)","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)"},"language":[{"iso":"eng"}],"date_published":"2022-07-11T00:00:00Z","doi":"10.1038/s41590-022-01257-4","intvolume":" 23","ddc":["570"],"page":"1246-1255","scopus_import":"1","acknowledgement":"This research was supported by the Scientific Service Units of IST Austria through resources provided by the Imaging and Optics, Electron Microscopy, Preclinical and Life Science Facilities. We thank C. Moussion for providing anti-PNAd antibody and D. Critchley for Talin1-floxed mice, and E. Papusheva for providing a custom 3D channel alignment script. This work was supported by a European Research Council grant ERC-CoG-72437 to M.S. M.H. was supported by Czech Sciencundation GACR 20-24603Y and Charles University PRIMUS/20/MED/013.","month":"07","department":[{"_id":"SiHi"},{"_id":"CaHe"},{"_id":"EdHa"},{"_id":"EM-Fac"},{"_id":"Bio"},{"_id":"MiSi"}],"publisher":"Springer Nature","isi":1,"citation":{"ista":"Assen FP, Abe J, Hons M, Hauschild R, Shamipour S, Kaufmann W, Costanzo T, Krens G, Brown M, Ludewig B, Hippenmeyer S, Heisenberg C-PJ, Weninger W, Hannezo EB, Luther SA, Stein JV, Sixt MK. 2022. Multitier mechanics control stromal adaptations in swelling lymph nodes. Nature Immunology. 23, 1246–1255.","chicago":"Assen, Frank P, Jun Abe, Miroslav Hons, Robert Hauschild, Shayan Shamipour, Walter Kaufmann, Tommaso Costanzo, et al. “Multitier Mechanics Control Stromal Adaptations in Swelling Lymph Nodes.” Nature Immunology. Springer Nature, 2022. https://doi.org/10.1038/s41590-022-01257-4.","ama":"Assen FP, Abe J, Hons M, et al. Multitier mechanics control stromal adaptations in swelling lymph nodes. Nature Immunology. 2022;23:1246-1255. doi:10.1038/s41590-022-01257-4","apa":"Assen, F. P., Abe, J., Hons, M., Hauschild, R., Shamipour, S., Kaufmann, W., … Sixt, M. K. (2022). Multitier mechanics control stromal adaptations in swelling lymph nodes. Nature Immunology. Springer Nature. https://doi.org/10.1038/s41590-022-01257-4","ieee":"F. P. Assen et al., “Multitier mechanics control stromal adaptations in swelling lymph nodes,” Nature Immunology, vol. 23. Springer Nature, pp. 1246–1255, 2022.","mla":"Assen, Frank P., et al. “Multitier Mechanics Control Stromal Adaptations in Swelling Lymph Nodes.” Nature Immunology, vol. 23, Springer Nature, 2022, pp. 1246–55, doi:10.1038/s41590-022-01257-4.","short":"F.P. Assen, J. Abe, M. Hons, R. Hauschild, S. Shamipour, W. Kaufmann, T. Costanzo, G. Krens, M. Brown, B. Ludewig, S. Hippenmeyer, C.-P.J. Heisenberg, W. Weninger, E.B. Hannezo, S.A. Luther, J.V. Stein, M.K. Sixt, Nature Immunology 23 (2022) 1246–1255."},"date_updated":"2023-08-02T06:53:07Z","author":[{"last_name":"Assen","first_name":"Frank P","full_name":"Assen, Frank P","id":"3A8E7F24-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0003-3470-6119"},{"first_name":"Jun","last_name":"Abe","full_name":"Abe, Jun"},{"orcid":"0000-0002-6625-3348","full_name":"Hons, Miroslav","id":"4167FE56-F248-11E8-B48F-1D18A9856A87","last_name":"Hons","first_name":"Miroslav"},{"last_name":"Hauschild","first_name":"Robert","full_name":"Hauschild, Robert","id":"4E01D6B4-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0001-9843-3522"},{"first_name":"Shayan","last_name":"Shamipour","full_name":"Shamipour, Shayan","id":"40B34FE2-F248-11E8-B48F-1D18A9856A87"},{"id":"3F99E422-F248-11E8-B48F-1D18A9856A87","full_name":"Kaufmann, Walter","orcid":"0000-0001-9735-5315","last_name":"Kaufmann","first_name":"Walter"},{"last_name":"Costanzo","first_name":"Tommaso","full_name":"Costanzo, Tommaso","id":"D93824F4-D9BA-11E9-BB12-F207E6697425","orcid":"0000-0001-9732-3815"},{"last_name":"Krens","first_name":"Gabriel","orcid":"0000-0003-4761-5996","id":"2B819732-F248-11E8-B48F-1D18A9856A87","full_name":"Krens, Gabriel"},{"first_name":"Markus","last_name":"Brown","id":"3DAB9AFC-F248-11E8-B48F-1D18A9856A87","full_name":"Brown, Markus"},{"first_name":"Burkhard","last_name":"Ludewig","full_name":"Ludewig, Burkhard"},{"last_name":"Hippenmeyer","first_name":"Simon","orcid":"0000-0003-2279-1061","full_name":"Hippenmeyer, Simon","id":"37B36620-F248-11E8-B48F-1D18A9856A87"},{"id":"39427864-F248-11E8-B48F-1D18A9856A87","full_name":"Heisenberg, Carl-Philipp J","orcid":"0000-0002-0912-4566","last_name":"Heisenberg","first_name":"Carl-Philipp J"},{"last_name":"Weninger","first_name":"Wolfgang","full_name":"Weninger, Wolfgang"},{"full_name":"Hannezo, Edouard B","id":"3A9DB764-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0001-6005-1561","first_name":"Edouard B","last_name":"Hannezo"},{"first_name":"Sanjiv A.","last_name":"Luther","full_name":"Luther, Sanjiv A."},{"last_name":"Stein","first_name":"Jens V.","full_name":"Stein, Jens V."},{"last_name":"Sixt","first_name":"Michael K","orcid":"0000-0002-4561-241X","id":"41E9FBEA-F248-11E8-B48F-1D18A9856A87","full_name":"Sixt, Michael K"}],"oa":1,"publication":"Nature Immunology","publication_identifier":{"issn":["1529-2908"],"eissn":["1529-2916"]},"day":"11","external_id":{"isi":["000822975900002"]},"title":"Multitier mechanics control stromal adaptations in swelling lymph nodes","project":[{"grant_number":"724373","_id":"25FE9508-B435-11E9-9278-68D0E5697425","call_identifier":"H2020","name":"Cellular navigation along spatial gradients"}],"has_accepted_license":"1","acknowledged_ssus":[{"_id":"Bio"},{"_id":"EM-Fac"},{"_id":"PreCl"},{"_id":"LifeSc"}],"_id":"9794","year":"2022","date_created":"2021-08-06T09:09:11Z","ec_funded":1,"abstract":[{"text":"Lymph nodes (LNs) comprise two main structural elements: fibroblastic reticular cells that form dedicated niches for immune cell interaction and capsular fibroblasts that build a shell around the organ. Immunological challenge causes LNs to increase more than tenfold in size within a few days. Here, we characterized the biomechanics of LN swelling on the cellular and organ scale. We identified lymphocyte trapping by influx and proliferation as drivers of an outward pressure force, causing fibroblastic reticular cells of the T-zone (TRCs) and their associated conduits to stretch. After an initial phase of relaxation, TRCs sensed the resulting strain through cell matrix adhesions, which coordinated local growth and remodeling of the stromal network. While the expanded TRC network readopted its typical configuration, a massive fibrotic reaction of the organ capsule set in and countered further organ expansion. Thus, different fibroblast populations mechanically control LN swelling in a multitier fashion.","lang":"eng"}],"file":[{"access_level":"open_access","creator":"dernst","checksum":"628e7b49809f22c75b428842efe70c68","content_type":"application/pdf","file_size":11475325,"date_updated":"2022-07-25T07:11:32Z","file_name":"2022_NatureImmunology_Assen.pdf","file_id":"11642","success":1,"relation":"main_file","date_created":"2022-07-25T07:11:32Z"}],"article_type":"original","publication_status":"published","article_processing_charge":"No","oa_version":"Published Version","quality_controlled":"1"}]