Jean Feydy
- Health data- and model- driven Knowledge Acquisition (HeKA)
Présentation
Domaines de recherche
Publications
Publications
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Untangling Vascular Trees for Surgery and Interventional RadiologyMICCAI 2025 - 28th International Conference on Medical Image Computing and Computer Assisted Intervention, Sep 2025, Daejeon, South Korea. pp.669-679, ⟨10.1007/978-3-032-05114-1_64⟩ |
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DiffMaSIF: Surface-based Protein-Protein Docking with Diffusion ModelsMachine Learning in Structural Biology workshop at NeurIPS 2023, Dec 2023, New Orleans, United States |
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Physics-informed deep neural network for rigid-body protein dockingMLDD 2022 - Machine Learning for Drug Discovery Workshop of ICLR 2022, Apr 2022, Virtual conference, France |
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Accurate Point Cloud Registration with Robust Optimal TransportNeurIPS 2021, Dec 2021, Virtual conference, France |
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Fast geometric learning with symbolic matricesThirty-fourth Conference on Neural Information Processing Systems, Dec 2020, Virtual-only, Canada |
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Fast and Scalable Optimal Transport for Brain TractogramsMICCAI 2019, Oct 2019, Shenzhen, China. ⟨10.1007/978-3-030-32248-9_71⟩ |
KeOps: Calcul rapide sur GPU dans les espaces à noyauxJournées de Statistique de la SFdS, May 2018, Palaiseau, France |
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Optimal Transport for Diffeomorphic RegistrationMICCAI 2017, Sep 2017, Quebec, Canada |
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SurvivalGPU: a GPU Powered Library for Scalable Survival Analysis in R and PythonAI4Health Summer School, Jun 2025, Paris, France |
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Accelerating High-Dimensional Temporal Modelling Using Graphics Processing Units for Pharmacovigilance Signal Detection on Real-Life DataChallenges of Trustable AI and Added-Value on Health, IOS Press, 2022, Studies in Health Technology and Informatics, ⟨10.3233/SHTI220401⟩ |
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Gromov-Wasserstein at Scale, Beyond Squared Norms2026 |
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Fast Large Deformation Matching with the Energy Distance Kernel2025 |
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Interpolating between Optimal Transport and MMD using Sinkhorn Divergences2018 |
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Global divergences between measures: from Hausdorff distance to Optimal Transport2018 |
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Analyse de données géométriques, au delà des convolutionsMathématiques générales [math.GM]. Université Paris-Saclay, 2020. Français. ⟨NNT : 2020UPASN017⟩ |