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  • Matthieu Kirchmeyer

  • PhD student
  • Team: MLIA

Publications

  • Matthieu Kirchmeyer. Out-of-distribution Generalization in Deep Learning : Classification and Spatiotemporal Forecasting. Computer Vision and Pattern Recognition [cs.CV]. Sorbonne Université, 2023. English. ⟨NNT : 2023SORUS080⟩. ⟨tel-04139066⟩
  • Yuan Yin, Matthieu Kirchmeyer, Jean-Yves Franceschi, Alain Rakotomamonjy, Patrick Gallinari. Continuous PDE Dynamics Forecasting with Implicit Neural Representations. The Eleventh International Conference on Learning Representations, May 2023, Kigali, Rwanda. . ⟨hal-04081163⟩
  • Yuan Yin, Matthieu Kirchmeyer, Jean-Yves Franceschi, Alain Rakotomamonjy, Patrick Gallinari. Continuous PDE Dynamics Forecasting with Implicit Neural Representations. The Eleventh International Conference on Learning Representations, International Conference on Representation Learning, May 2023, Kigali, Rwanda. ⟨hal-03792179v2⟩
  • Alexandre Rame, Matthieu Kirchmeyer, Thibaud Rahier, Alain Rakotomamonjy, Patrick Gallinari, et al.. Diverse Weight Averaging for Out-of-Distribution Generalization. Conference on Neural Information Processing Systems, Nov 2022, New-Orleans, United States. ⟨hal-03891267⟩
  • Matthieu Kirchmeyer, Yuan Yin, Jérémie Donà, Nicolas Baskiotis, Alain Rakotomamonjy, et al.. Generalizing to New Physical Systems via Context-Informed Dynamics Model. International Conference on Machine Learning, Jul 2022, Baltimore, France. ⟨hal-03547546v2⟩
  • Matthieu Kirchmeyer, Alain Rakotomamonjy, Emmanuel de Bezenac, Patrick Gallinari. Mapping conditional distributions for domain adaptation under generalized target shift. International Conference on Learning Representations, Apr 2022, Virtual, Unknown Region. ⟨hal-03396183v3⟩