1) Latent Representation Matters: Human-like Sketches in One-shot Drawing Tasks. Victor Boutin, Rishav Mukherji, Aditya Agrawal, Sabine Muzellec, Thomas FEL, Thomas Serre, Rufin VanRullen, Neurips 2024
2) Understanding Visual Feature Reliance through the Lens of Complexity: Thomas FEL, Louis Béthune, Andrew Lampinen, Thomas Serre, Katherine Hermann, Neurips 2024
3) Beyond the Doors of Perception: Vision Transformers Represent Relations Between ObjectsMichael Lepori, Alexa Tartaglini, Wai Keen Vong, Thomas Serre, Brenden Lake, Ellie Pavlick, Neurips 2024
4) RTify: Aligning Deep Neural Networks with Human Behavioral Decisions: Yu-Ang Cheng, Ivan F Rodriguez Rodriguez, Sixuan Chen, Takeo Watanabe, Thomas Serre, Neurips 2024
5) Combining Statistical Depth and Fermat Distance for Uncertainty QuantificationHai: Vy Nguyen, Fabrice Gamboa, Reda CHHAIBI, Sixin Zhang, Serge Gratton, Thierry Giaccone, Neurips 2024
6) Blending Neural Operators and Relaxation Methods in PDE Numerical Solvers:
Enrui Zhang, Adar Kahana, Alena Kopaničáková, Eli Turkel, Rishikesh Ranade, Jay Pathak, George Em Karniadakis, Nature Machine Intelligence 2024
7) Time-Constrained Robust MDPs.: Adil Zouitine, David Bertoin, Pierre Clavier, Matthieu Geist, Emmanuel Rachelson, NeurIPS 2024.
8) Fair online bilateral trade. Francois Bachoc, Nicolo Cesa-Bianchi, Tommaso Cesari and Roberto Colomboni, NeurIPS 2024.
9) Swarm gradient dynamics for global optimization: the mean-field limit case, J. Bolte, L. Miclo, S. Villeneuve, Volume 205, pages 661–701, 2024
10) Differentiating Nonsmooth Solutions to Parametric Monotone Inclusion Problems, J. Bolte, E. Pauwels, A. Silvetti-Falls, Volume 34, Issue 1, pp. 1-1185, 2024
11) What is the Long-Run Distribution of SGD? A Large Deviations Analysis, Waïss Azizian, Franck Iutzeler, Jérôme Malick, Panayotis Mertikopoulos, ICML 2024.
12) Derivatives of Stochastic Gradient Descent, Franck Iutzeler, Edouard Pauwels, Samuel Vaiter, NeurIPS 2024
13) One-step differentiation of iterative algorithms, Jérôme Bolte, Edouard Pauwels, Samuel Vaiter, Neurips 2023.
14) Machine culture. Levin Brinkmann et al, Nature Human Behaviour 2023
15) Trust within human-machine collectives depends on the perceived consensus about cooperative norms. Kinga Makovi, Anahit Sargsyan, Wendi Li, Jean-François Bonnefon, Talal Rahwan, Nature Communications 2023
16) Transport-based counterfactual models. Journal of Machine Learning Research, 25(136), 1-59. De Lara, L., González-Sanz, A., Asher, N., Risser, L., & Loubes, J. M. (2024).
17) Achieving robustness in classification using optimal transport with hinge regularization. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (pp. 505-514): Serrurier, M., Mamalet, F., González-Sanz, A., Boissin, T., Loubes, J. M., & Del Barrio, E. (2021).
18) Self-supervised spatio-temporal representation learning of satellite image time series. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, (), 1–18. Dumeur, I., Valero, S., & Inglada, J. (2024).
19) Physics-constrained deep learning for biophysical parameter retrieval from sentinel-2 images: inversion of the prosail model. Remote Sensing of Environment, 312(), 114309. Yoël Zérah, Valero, S., & Inglada, J. (2024).
20) Leveraging Argumentation for Generating Robust Sample-based Explanations. IJCAI 2023: 3104-3111. Leila Amgoud, Philippe Muller, Henri Trenquier.
21) Characterisations of Sample-based Explainers. ECAI 2024: 770-777. Leila Amgoud, Martin C. Cooper, Salim Debbaoui. Axiomatic
22) DP-SGD Without Clipping: The Lipschitz Neural Network Way
Louis Béthune, Thomas Massena, Thibaut Boissin, Yannick Prudent, Corentin Friedrich, Franck Mamalet, Aurélien Bellet, Mathieu Serrurier, David Vigouroux, Corentin Friedrich
ICLR 2024 – 12th International Conference on Learning Representations, 2024, Vienna (Austria), Austria
23) Straight-Through meets Sparse Recovery: the Support Exploration Algorithm
Mimoun Mohamed, François Malgouyres, Valentin Emiya, Caroline Chaux
ICML 2024, the 41st International Conference on Machine Learning, Jul 2024, Vienna, Austria
24) On the Feasibility of EASA Learning Assurance Objectives for Machine Learning Components
Florence de Grancey, Sébastien Gerchinovitz, Lucian Alecu, Hugues Bonnin, Joseba Dalmau, Kevin Delmas, Franck Mamalet
ERTS 2024, Jun 2024, Toulouse, France
25) How to design a dataset compliant with an ML-based system ODD?
Cyril Cappi, Noémie Cohen, Mélanie Ducoffe, Christophe Gabreau, Laurent Gardes, Adrien Gauffriau, Jean-Brice Ginestet, Franck Mamalet, Vincent Mussot, Claire Pagetti, David Vigouroux
12th European Congress on Embedded Real Time Software and Systems, Jun 2024, Toulouse, France