115

404

• 
  Nicolas Bereux, Aurélien Decelle, Cyril Furtlehner, Lorenzo Rosset, Beatriz Seoane. Fast training and sampling of Restricted Boltzmann Machines. 13th International Conference on Learning Representations - ICLR 2025, Apr 2025, Singaour, Singapore. ⟨hal-04885777⟩
• 
  Nilo Schwencke, Cyril Furtlehner. ANAGRAM: a natural gradient relative to adapted model for efficient PINNS learning. ICLR 2025 - International Conference on Learning Representations, Apr 2025, Singapour, Singapore. ⟨hal-04918272⟩
• 
  Nicolas Atienza, Christophe Labreuche, Johanne Cohen, Michèle Sebag. Provably Safeguarding a Classifier from OOD and Adversarial Samples: an Extreme Value Theory Approach. ICLR 2025 - The Thirteenth International Conference on Learning Representations, Apr 2025, Singapore (SG), Singapore. ⟨hal-04922382⟩
• 
  Stella Douka, Manon Verbockhaven, Théo Rudkiewicz, Stéphane Rivaud, François P. Landes, et al.. Growth strategies for arbitrary DAG neural architectures. ESANN 2025 - 33th European Symposium on Artificial Neural Networks, Apr 2025, Bruges, Belgium. ⟨hal-04902059⟩
• 
  Alessandro Leite, Marc Schoenauer. Memetic Semantic Boosting for Symbolic Regression. Genetic Programming and Evolvable Machines, In press. ⟨hal-04911540⟩
• 
  Francesco Pezzicoli. Statistical Physics - Machine Learning Interplay : from Addressing Class Imbalance with Replica Theory to Predicting Dynamical Heterogeneities with SE(3)-equivariant Graph Neural Networks. Machine Learning [cs.LG]. Université Paris-Saclay, 2024. English. ⟨NNT : 2024UPASG115⟩. ⟨tel-04910839⟩
• 
  Nilo Schwencke, Cyril Furtlehner. ANaGRAM: A Natural Gradient Relative to Adapted Model for efficient PINNs learning. 2024. ⟨hal-04849532⟩
• 
  Matthieu Kowalski, Benoît Malézieux, Thomas Moreau, Audrey Repetti. Analysis and synthesis denoisers for forward-backward plug-and-play algorithms. 2024. ⟨hal-04786802v3⟩
• 
  Apolline Mellot, Antoine Collas, Sylvain Chevallier, Alexandre Gramfort, Denis Engemann. Geodesic optimization for predictive shift adaptation on EEG data. NeurIPS 2024 - 38th Conference on Neural Information Processing Systems, Dec 2024, Vancouver, Canada. ⟨hal-04902523⟩
• 
  Dimitrios Bachtis, Giulio Biroli, Aurélien Decelle, Beatriz Seoane. Cascade of phase transitions in the training of Energy-based models. NeurIPS 2024 - 38th Annual Conference on Neural Information Processing Systems, Dec 2024, Vancouver, Canada. ⟨10.48550/arXiv.2405.14689⟩. ⟨hal-04897693⟩
• 
  Mouadh Yagoubi, David Danan, Milad Leyli-Abadi, Jean-Patrick Brunet, Maroua Gmati, et al.. NeurIPS 2024 ML4CFD Competition: Harnessing Machine Learning for Computational Fluid Dynamics in Airfoil Design. NeurIPS 2024 - The 38th Annual Conference on Neural Information Processing Systems, Dec 2024, Vancouver, Canada. ⟨hal-04869170⟩
• 
  Sebastien Treguer, Marc Schoenauer. Lessons learned from TAILOR benchmarks/challenges. INRIA - team TAU. 2024. ⟨hal-04923991⟩
• 
  Michele Quattromini, Michele Alessandro Bucci, Stefania Cherubini, Onofrio Semeraro. Graph Neural Networks and Differential Equations: A hybrid approach for data assimilation of fluid flows. 2024. ⟨hal-04794444⟩
• 
  Benoît Malézieux, Florent Michel, Thomas Moreau, Matthieu Kowalski. Where prior learning can and can't work in unsupervised inverse problems. 2024. ⟨hal-04782335⟩
• 
  Pierre Barbault, Matthieu Kowalski, Charles Soussen. Bernoulli and Gauss Take a Look at the MAP. 2024. ⟨hal-04782425⟩
• 
  Manon Verbockhaven, Théo Rudkiewicz, Sylvain Chevallier, Guillaume Charpiat. Growing Tiny Networks: Spotting Expressivity Bottlenecks and Fixing Them Optimally. Transactions on Machine Learning Research Journal, 2024. ⟨hal-04591472v2⟩
• 
  Mariia Zameshina, Mathurin Videau, Alessandro Leite, Marc Schoenauer, Laurent Najman, et al.. Agnostic latent diversity enhancement in generative modeling. 2024. ⟨hal-04661473v2⟩
• 
  Igor Carrara, Bruno Aristimunha, Marie-Constance Corsi, Raphael Yokoingawa de Camargo, Sylvain Chevallier, et al.. Geometric Neural Network based on Phase Space for BCI decoding. Journal of Neural Engineering, 2024, ⟨10.1088/1741-2552/ad88a2⟩. ⟨hal-04500580⟩
• 
  Mathurin Videau, Mariia Zameshina, Alessandro Leite, Laurent Najman, Marc Schoenauer, et al.. Evolutionary Retrofitting. 2024. ⟨hal-04733511⟩
• 
  Sébastien Velut, Sylvain Chevallier, Marie-Constance Corsi, Frédéric Dehais. Deep Riemannian Neural Architectures for Domain Adaptation in Burst cVEP-based Brain Computer Interface. ESANN 2024 - 32nd European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, Oct 2024, Bruges, Belgium. pp.571-576, ⟨10.14428/esann/2024.ES2024-112⟩. ⟨hal-04720928⟩
• 
  Thibault Monsel, Emmanuel Menier, Lionel Mathelin, Onofrio Semeraro, Guillaume Charpiat. Neural DDEs with Learnable Delays for Partially Observed Dynamical Systems. 2024. ⟨hal-04715748⟩
• 
  Thibault Monsel, Onofrio Semeraro, Lionel Mathelin, Guillaume Charpiat. Time and State Dependent Neural Delay Differential Equations. ML-DE@ECAI 2024 : Machine Learning Meets Differential Equations: From Theory to Applications, Sep 2024, Santiago de compostela, Galicia, Spain. ⟨hal-04794450⟩
• 
  Thibault Monsel, Onofrio Semeraro, Lionel Mathelin, Guillaume Charpiat. Time and State Dependent Neural Delay Differential Equations. ML-DE@ECAI 2024 : Machine Learning Meets Differential Equations: From Theory to Applications, Sep 2024, Santiago de compostela, Galicia, Spain. ⟨hal-04794800⟩
• 
  Alice Lacan, Blaise Hanczar, Michele Sebag. Frugal Generative Modeling for Tabular Data. ECML PKDD 2024 - European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, Sep 2024, Vilnius, Lithuania. pp.55--72, ⟨10.1007/978-3-031-70371-3_4⟩. ⟨hal-04705131⟩
• 
  Eva Boguslawski, Alessandro Leite, Benjamin Donnot, Matthieu Dussartre, Marc Schoenauer. Emulation of Zonal Controllers for the Power System Transport Problem. ML4SPS 2024 - Machine Learning for Sustainable Power Systems ECML 2024 Workshop, European Conference of Machine Learning, Sep 2024, Vilnius, Lithuania. ⟨hal-04924271⟩
• 
  Dylan Sechet, Francesca Bugiotti, Matthieu Kowalski, Edouard D’hérouville, Filip Langiewicz. A Hierarchical Deep Learning Approach for Minority Instrument Detection. DAFx 2024 - the 27th International Conference on Digital Audio Effects, Sep 2024, Guildford Surrey, United Kingdom. ⟨hal-04793160⟩
• 
  Manh Hung Nguyen, Lisheng Sun-Hosoya, Isabelle Guyon. Meta-Learning from Learning Curves for Budget-Limited Algorithm Selection. Pattern Recognition Letters, 2024, 185, pp.225-231. ⟨10.1016/j.patrec.2024.08.010⟩. ⟨hal-04719035⟩
• 
  Thibault de Surrel, Sylvain Chevallier, Fabien Lotte, Florian Yger. Averaging trajectories on the manifold of symmetric positive definite matrices. EUSIPCO 2024 - 32nd European Signal Processing Conference, Aug 2024, Lyon, France. ⟨hal-04708878⟩
• 
  Bruno Aristimunha, Raphael de Camargo, Walter Pinaya, Sylvain Chevallier, Alexandre Gramfort, et al.. Evaluating the structure of cognitive tasks with transfer learning. 2024. ⟨hal-04677674⟩
• 
  Isabelle Hoxha, Sylvain Chevallier, Arnaud Delorme, Michel-Ange Amorim. EEG anticipatory activity depends on sensory modality. 2024. ⟨hal-04677650⟩