Pré-publication, Document de travail
AO
Affichage des résultats 1 à 12 sur 611 au total
AO : 1 à 12 sur 611 au total
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Article dans une revue
Bruna Lopes, Gabriel Schwartz, Sylvain Chevallier, Raphael Y de Camargo, Bruno Aristimunha. Learning aligned EEG representations with subject-specific encoders. Scientific Reports, 2026, ⟨10.1038/s41598-026-69220-z⟩. ⟨hal-05758650⟩
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Communication dans un congrès
Sébastien Velut, Stella Douka, Théo Rudkiewicz, Alex Davey, Stéphane Rivaud, et al.. Tackling brain signal inter-subject variability with adaptive neural architectures. IJCNN 2026 - 2026 International Joint Conference on Neural Network, IEEE, Jun 2026, Maastricht, Netherlands. ⟨hal-05752385⟩
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Article dans une revue
Léo Planche, Anna Ilina, María C Ávila-Arcos, Flora Jay, Emilia Huerta-Sanchez, et al.. An archaic reference-free method to jointly infer Neanderthal and Denisovan introgressed segments in modern human genomes. Molecular Biology and Evolution, 2025, ⟨10.1101/2025.03.17.643330⟩. ⟨hal-05747173⟩
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Article dans une revue
Marco Rosario Capodiferro, Léo Planche, Emily M Breslin, Linda Ongaro, María C Ávila-Arcos, et al.. Archaic ancestry inference in imputed ancient human genomes. Nature Communications, 2026, 17 (1), pp.9480. ⟨10.1038/s41467-026-76204-0⟩. ⟨hal-05747161⟩
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Communication dans un congrès
Dylan Sechet, Marc Evrard, Matthieu Kowalski. Simulation-Based Inference for Plate Reverb System Identification. DAFX 2026 - 29th International Conference on Digital Audio Effects, Sep 2026, Cambridge, United States. ⟨hal-05742718⟩
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Communication dans un congrès
Brahim Driss, Alex Davey, Riad Akrour. PB$^2$: Preference Space Exploration via Population-Based Methods in Preference-Based Reinforcement Learning. RLC 2026 - Third Reinforcement Learning Conference, Aug 2026, Montreal, Canada. ⟨hal-05732524⟩
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Logiciel
Alexandre Barachant, Quentin Barthélemy, Gabriel Wagner Vom Berg, Alexandre Gramfort, Sylvain Chevallier, et al.. pyRiemann. 2026, ⟨swh:1:dir:99d04d80bb390054f73700b971236958727e9c55;origin=https://github.com/pyRiemann/pyRiemann;visit=swh:1:snp:42707203ccd68219f2c48dd52388fdaf0c91a420;anchor=swh:1:rev:854804d34bc7b40b318323520be896d97d8aa859⟩. ⟨hal-05676137⟩
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Logiciel
Grégoire Cattan, Quentin Barthélemy, Anton Andreev, Sylvain Chevallier, Vedant Patare, et al.. pyRiemann-qiskit. 2026, ⟨swh:1:dir:8b5612aedfe0d134a3dab99d574106412915ae4d;origin=https://github.com/pyRiemann/pyRiemann-qiskit;visit=swh:1:snp:9dfc0df92cc1fa97758f76c4b7b2f7314973f773;anchor=swh:1:rev:14df49d9c2bfed5372f8f59b5b8fa7120dfd1b6f⟩. ⟨hal-05676343⟩
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Communication dans un congrès
Bruno Aristimunha, Dung Truong, Pierre Guetschel, Seyed Yahya Shirazi, Isabelle Guyon, et al.. EEG Foundation Challenge: From Cross-Task to Cross-Subject EEG Decoding. NeurIPS 2025 - Thirty-Ninth Annual Conference on Neural Information Processing Systems, Competition Track, Nov 2025, San Diego, United States. ⟨hal-05714360⟩
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Article dans une revue
Alice Lacan, Romain André, Michèle Sebag, Blaise Hanczar. In silico generation of gene expression profiles using diffusion models. BMC Bioinformatics, 2026, 27 (1), pp.160. ⟨10.1186/s12859-026-06470-8⟩. ⟨hal-05714728⟩
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Pré-publication, Document de travail
Bruno Aristimunha, Ce Ju, Antoine Collas, Florent Bouchard, Ammar Mian, et al.. SPD Learn: A Geometric Deep Learning Python Library for Neural Decoding Through Trivialization. 2026. ⟨hal-05714371⟩