--- _id: '14173' abstract: - lang: eng 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." alternative_title: - Advances in Neural Information Processing Systems article_processing_charge: No arxiv: 1 author: - first_name: Florian full_name: Wenzel, Florian last_name: Wenzel - first_name: Andrea full_name: Dittadi, Andrea last_name: Dittadi - first_name: Peter Vincent full_name: Gehler, Peter Vincent last_name: Gehler - first_name: Carl-Johann Simon-Gabriel full_name: Carl-Johann Simon-Gabriel, Carl-Johann Simon-Gabriel last_name: Carl-Johann Simon-Gabriel - first_name: Max full_name: Horn, Max last_name: Horn - first_name: Dominik full_name: Zietlow, Dominik last_name: Zietlow - first_name: David full_name: Kernert, David last_name: Kernert - first_name: Chris full_name: Russell, Chris last_name: Russell - first_name: Thomas full_name: Brox, Thomas last_name: Brox - first_name: Bernt full_name: Schiele, Bernt last_name: Schiele - first_name: Bernhard full_name: Schölkopf, Bernhard last_name: Schölkopf - first_name: Francesco full_name: Locatello, Francesco id: 26cfd52f-2483-11ee-8040-88983bcc06d4 last_name: Locatello orcid: 0000-0002-4850-0683 citation: 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.' 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.' 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. 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. 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.' 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. 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. conference: end_date: 2022-12-09 location: New Orleans, LA, United States name: 'NeurIPS: Neural Information Processing Systems' start_date: 2022-11-28 date_created: 2023-08-22T14:01:13Z date_published: 2022-12-15T00:00:00Z date_updated: 2023-09-06T10:34:43Z day: '15' department: - _id: FrLo extern: '1' external_id: arxiv: - '2207.09239' intvolume: ' 35' language: - iso: eng main_file_link: - open_access: '1' url: https://arxiv.org/abs/2207.09239 month: '12' oa: 1 oa_version: Preprint page: 7181-7198 publication: 36th Conference on Neural Information Processing Systems publication_identifier: isbn: - '9781713871088' publication_status: published publisher: Neural Information Processing Systems Foundation quality_controlled: '1' scopus_import: '1' status: public title: Assaying out-of-distribution generalization in transfer learning type: conference user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 35 year: '2022' ... --- _id: '14174' 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 arxiv: 1 author: - first_name: Andrea full_name: Dittadi, Andrea last_name: Dittadi - first_name: Frederik full_name: Träuble, Frederik last_name: Träuble - first_name: Manuel full_name: Wüthrich, Manuel last_name: Wüthrich - first_name: Felix full_name: Widmaier, Felix last_name: Widmaier - first_name: Peter full_name: Gehler, Peter last_name: Gehler - first_name: Ole full_name: Winther, Ole last_name: Winther - first_name: Francesco full_name: Locatello, Francesco id: 26cfd52f-2483-11ee-8040-88983bcc06d4 last_name: Locatello orcid: 0000-0002-4850-0683 - first_name: Olivier full_name: Bachem, Olivier last_name: Bachem - first_name: Bernhard full_name: Schölkopf, Bernhard last_name: Schölkopf - first_name: Stefan full_name: Bauer, Stefan last_name: Bauer citation: 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. 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. 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. 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. 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. conference: end_date: 2022-04-29 location: Virtual name: 'ICLR: International Conference on Learning Representations' start_date: 2022-04-25 date_created: 2023-08-22T14:02:13Z date_published: 2022-04-25T00:00:00Z date_updated: 2023-09-11T09:48:36Z day: '25' department: - _id: FrLo extern: '1' external_id: arxiv: - '2107.05686' language: - iso: eng main_file_link: - open_access: '1' url: ' https://doi.org/10.48550/arXiv.2107.05686' month: '04' oa: 1 oa_version: Preprint publication: 10th International Conference on Learning Representations publication_status: published quality_controlled: '1' status: public title: The role of pretrained representations for the OOD generalization of reinforcement learning agents type: conference user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 year: '2022' ... --- _id: '14175' 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." article_processing_charge: No arxiv: 1 author: - first_name: Osama full_name: Makansi, Osama last_name: Makansi - first_name: Julius von full_name: Kügelgen, Julius von last_name: Kügelgen - first_name: Francesco full_name: Locatello, Francesco id: 26cfd52f-2483-11ee-8040-88983bcc06d4 last_name: Locatello orcid: 0000-0002-4850-0683 - first_name: Peter full_name: Gehler, Peter last_name: Gehler - first_name: Dominik full_name: Janzing, Dominik last_name: Janzing - first_name: Thomas full_name: Brox, Thomas last_name: Brox - first_name: Bernhard full_name: Schölkopf, Bernhard last_name: Schölkopf citation: 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.' 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.' 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.' ieee: 'O. Makansi et al., “You mostly walk alone: Analyzing feature attribution in trajectory prediction,” in 10th International Conference on Learning Representations, Virtual, 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.' mla: 'Makansi, Osama, et al. “You Mostly Walk Alone: Analyzing Feature Attribution in Trajectory Prediction.” 10th International Conference on Learning Representations, 2022.' short: O. Makansi, J. von Kügelgen, F. Locatello, P. Gehler, D. Janzing, T. Brox, B. Schölkopf, in:, 10th International Conference on Learning Representations, 2022. conference: end_date: 2022-04-29 location: Virtual name: 'ICLR: International Conference on Learning Representations' start_date: 2022-04-25 date_created: 2023-08-22T14:02:34Z date_published: 2022-04-25T00:00:00Z date_updated: 2023-09-11T09:52:20Z day: '25' department: - _id: FrLo extern: '1' external_id: arxiv: - '2110.05304' language: - iso: eng main_file_link: - open_access: '1' url: https://doi.org/10.48550/arXiv.2110.05304 month: '04' oa: 1 oa_version: Preprint publication: 10th International Conference on Learning Representations publication_status: published quality_controlled: '1' status: public title: 'You mostly walk alone: Analyzing feature attribution in trajectory prediction' type: conference user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 year: '2022' ... --- _id: '14215' abstract: - lang: eng 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. article_processing_charge: No arxiv: 1 author: - first_name: Nasim full_name: Rahaman, Nasim last_name: Rahaman - first_name: Martin full_name: Weiss, Martin last_name: Weiss - first_name: Frederik full_name: Träuble, Frederik last_name: Träuble - first_name: Francesco full_name: Locatello, Francesco id: 26cfd52f-2483-11ee-8040-88983bcc06d4 last_name: Locatello orcid: 0000-0002-4850-0683 - first_name: Alexandre full_name: Lacoste, Alexandre last_name: Lacoste - first_name: Yoshua full_name: Bengio, Yoshua last_name: Bengio - first_name: Chris full_name: Pal, Chris last_name: Pal - first_name: Li Erran full_name: Li, Li Erran last_name: Li - first_name: Bernhard full_name: Schölkopf, Bernhard last_name: Schölkopf citation: 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.' 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. 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. 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. 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. 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. conference: end_date: 2022-12-09 location: New Orleans, LA, United States name: 'NeurIPS: Neural Information Processing Systems' start_date: 2022-11-28 date_created: 2023-08-22T14:21:47Z date_published: 2022-11-04T00:00:00Z date_updated: 2023-09-13T09:35:59Z day: '04' department: - _id: FrLo extern: '1' external_id: arxiv: - '2211.02348' language: - iso: eng main_file_link: - open_access: '1' url: https://doi.org/10.48550/arXiv.2211.02348 month: '11' oa: 1 oa_version: Preprint publication: 36th Conference on Neural Information Processing Systems publication_status: submitted quality_controlled: '1' status: public title: A general purpose neural architecture for geospatial systems type: conference 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: '14220' 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. article_number: '2201.13388' article_processing_charge: No arxiv: 1 author: - first_name: Davide full_name: Mambelli, Davide last_name: Mambelli - first_name: Frederik full_name: Träuble, Frederik last_name: Träuble - first_name: Stefan full_name: Bauer, Stefan last_name: Bauer - first_name: Bernhard full_name: Schölkopf, Bernhard last_name: Schölkopf - first_name: Francesco full_name: Locatello, Francesco id: 26cfd52f-2483-11ee-8040-88983bcc06d4 last_name: Locatello orcid: 0000-0002-4850-0683 citation: 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 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. ieee: D. Mambelli, F. Träuble, S. Bauer, B. Schölkopf, and F. Locatello, “Compositional multi-object reinforcement learning with linear relation networks,” arXiv. . ista: Mambelli D, Träuble F, Bauer S, Schölkopf B, Locatello F. Compositional multi-object reinforcement learning with linear relation networks. 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. short: D. Mambelli, F. Träuble, S. Bauer, B. Schölkopf, F. Locatello, ArXiv (n.d.). date_created: 2023-08-22T14:23:16Z date_published: 2022-01-31T00:00:00Z date_updated: 2023-09-11T11:49:40Z day: '31' department: - _id: FrLo doi: 10.48550/arXiv.2201.13388 extern: '1' external_id: arxiv: - '2201.13388' language: - iso: eng main_file_link: - open_access: '1' url: https://doi.org/10.48550/arXiv.2201.13388 month: '01' oa: 1 oa_version: Preprint publication: arXiv publication_status: submitted status: public title: Compositional multi-object reinforcement learning with linear relation networks 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' license: https://creativecommons.org/publicdomain/zero/1.0/ 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' ... --- _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 license: https://creativecommons.org/licenses/by/4.0/ 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: '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: '9649' abstract: - lang: eng 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." 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." article_processing_charge: Yes (via OA deal) article_type: original author: - first_name: Jean-Daniel full_name: Boissonnat, Jean-Daniel last_name: Boissonnat - first_name: Mathijs full_name: Wintraecken, Mathijs id: 307CFBC8-F248-11E8-B48F-1D18A9856A87 last_name: Wintraecken orcid: 0000-0002-7472-2220 citation: 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 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 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. 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. 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. short: J.-D. Boissonnat, M. Wintraecken, Foundations of Computational Mathematics 22 (2022) 967–1012. date_created: 2021-07-14T06:44:53Z date_published: 2022-01-01T00:00:00Z date_updated: 2023-08-02T06:49:17Z day: '01' ddc: - '516' department: - _id: HeEd doi: 10.1007/s10208-021-09520-0 ec_funded: 1 external_id: isi: - '000673039600001' file: - access_level: open_access checksum: f1d372ec3c08ec22e84f8e93e1126b8c content_type: application/pdf creator: mwintrae date_created: 2021-07-14T06:44:36Z date_updated: 2021-07-14T06:44:36Z file_id: '9650' file_name: Boissonnat-Wintraecken2021_Article_TheTopologicalCorrectnessOfPLA.pdf file_size: 1455699 relation: main_file file_date_updated: 2021-07-14T06:44:36Z has_accepted_license: '1' intvolume: ' 22' isi: 1 language: - iso: eng month: '0' oa: 1 oa_version: Published Version page: 967-1012 project: - _id: 260C2330-B435-11E9-9278-68D0E5697425 call_identifier: H2020 grant_number: '754411' name: ISTplus - Postdoctoral Fellowships publication: 'Foundations of Computational Mathematics ' publication_identifier: eissn: - 1615-3383 publication_status: published publisher: Springer Nature quality_controlled: '1' related_material: record: - id: '7952' relation: earlier_version status: public scopus_import: '1' status: public title: The topological correctness of PL approximations of isomanifolds 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: 22 year: '2022' ... --- _id: '9794' abstract: - lang: eng 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.' acknowledged_ssus: - _id: Bio - _id: EM-Fac - _id: PreCl - _id: LifeSc 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. article_processing_charge: No article_type: original author: - first_name: Frank P full_name: Assen, Frank P id: 3A8E7F24-F248-11E8-B48F-1D18A9856A87 last_name: Assen orcid: 0000-0003-3470-6119 - first_name: Jun full_name: Abe, Jun last_name: Abe - first_name: Miroslav full_name: Hons, Miroslav id: 4167FE56-F248-11E8-B48F-1D18A9856A87 last_name: Hons orcid: 0000-0002-6625-3348 - first_name: Robert full_name: Hauschild, Robert id: 4E01D6B4-F248-11E8-B48F-1D18A9856A87 last_name: Hauschild orcid: 0000-0001-9843-3522 - first_name: Shayan full_name: Shamipour, Shayan id: 40B34FE2-F248-11E8-B48F-1D18A9856A87 last_name: Shamipour - first_name: Walter full_name: Kaufmann, Walter id: 3F99E422-F248-11E8-B48F-1D18A9856A87 last_name: Kaufmann orcid: 0000-0001-9735-5315 - first_name: Tommaso full_name: Costanzo, Tommaso id: D93824F4-D9BA-11E9-BB12-F207E6697425 last_name: Costanzo orcid: 0000-0001-9732-3815 - first_name: Gabriel full_name: Krens, Gabriel id: 2B819732-F248-11E8-B48F-1D18A9856A87 last_name: Krens orcid: 0000-0003-4761-5996 - first_name: Markus full_name: Brown, Markus id: 3DAB9AFC-F248-11E8-B48F-1D18A9856A87 last_name: Brown - first_name: Burkhard full_name: Ludewig, Burkhard last_name: Ludewig - first_name: Simon full_name: Hippenmeyer, Simon id: 37B36620-F248-11E8-B48F-1D18A9856A87 last_name: Hippenmeyer orcid: 0000-0003-2279-1061 - first_name: Carl-Philipp J full_name: Heisenberg, Carl-Philipp J id: 39427864-F248-11E8-B48F-1D18A9856A87 last_name: Heisenberg orcid: 0000-0002-0912-4566 - first_name: Wolfgang full_name: Weninger, Wolfgang last_name: Weninger - first_name: Edouard B full_name: Hannezo, Edouard B id: 3A9DB764-F248-11E8-B48F-1D18A9856A87 last_name: Hannezo orcid: 0000-0001-6005-1561 - first_name: Sanjiv A. full_name: Luther, Sanjiv A. last_name: Luther - first_name: Jens V. full_name: Stein, Jens V. last_name: Stein - first_name: Michael K full_name: Sixt, Michael K id: 41E9FBEA-F248-11E8-B48F-1D18A9856A87 last_name: Sixt orcid: 0000-0002-4561-241X citation: 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 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. 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. 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. 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_created: 2021-08-06T09:09:11Z date_published: 2022-07-11T00:00:00Z date_updated: 2023-08-02T06:53:07Z day: '11' ddc: - '570' department: - _id: SiHi - _id: CaHe - _id: EdHa - _id: EM-Fac - _id: Bio - _id: MiSi doi: 10.1038/s41590-022-01257-4 ec_funded: 1 external_id: isi: - '000822975900002' file: - access_level: open_access checksum: 628e7b49809f22c75b428842efe70c68 content_type: application/pdf creator: dernst date_created: 2022-07-25T07:11:32Z date_updated: 2022-07-25T07:11:32Z file_id: '11642' file_name: 2022_NatureImmunology_Assen.pdf file_size: 11475325 relation: main_file success: 1 file_date_updated: 2022-07-25T07:11:32Z has_accepted_license: '1' intvolume: ' 23' isi: 1 language: - iso: eng month: '07' oa: 1 oa_version: Published Version page: 1246-1255 project: - _id: 25FE9508-B435-11E9-9278-68D0E5697425 call_identifier: H2020 grant_number: '724373' name: Cellular navigation along spatial gradients publication: Nature Immunology publication_identifier: eissn: - 1529-2916 issn: - 1529-2908 publication_status: published publisher: Springer Nature quality_controlled: '1' scopus_import: '1' status: public title: Multitier mechanics control stromal adaptations in swelling lymph 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: journal_article user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8 volume: 23 year: '2022' ...