Matthieu Kirchmeyer

According to our database, Matthieu Kirchmeyer authored at least 10 papers between 2019 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

Unified all-atom molecule generation with neural fields.

Matthieu Kirchmeyer, Pedro O. Pinheiro, Emma Willett, Karolis Martinkus, Joseph Kleinhenz, Emily K. Makowski, Andrew M. Watkins, Vladimir Gligorijevic, Richard Bonneau, Saeed Saremi

CoRR, November, 2025

2024

Antibody DomainBed: Out-of-Distribution Generalization in Therapeutic Protein Design.

Natasa Tagasovska, Ji Won Park, Matthieu Kirchmeyer, Nathan C. Frey, Andrew Martin Watkins, Aya Abdelsalam Ismail, Arian Rokkum Jamasb, Edith Lee, Tyler Bryson, Stephen Ra, Kyunghyun Cho

CoRR, 2024

Score-based 3D molecule generation with neural fields.

Matthieu Kirchmeyer, Pedro O. Pinheiro, Saeed Saremi

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

2023

Out-of-distribution Generalization in Deep Learning : Classification and Spatiotemporal Forecasting. (Généralisation hors-distribution en apprentissage profond : classification et prévision spatiotemporelle).

Matthieu Kirchmeyer

PhD thesis, 2023

Continuous PDE Dynamics Forecasting with Implicit Neural Representations.

Yuan Yin, Matthieu Kirchmeyer, Jean-Yves Franceschi, Alain Rakotomamonjy, Patrick Gallinari

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Diverse Weight Averaging for Out-of-Distribution Generalization.

Alexandre Ramé, Matthieu Kirchmeyer, Thibaud Rahier, Alain Rakotomamonjy, Patrick Gallinari, Matthieu Cord

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Generalizing to New Physical Systems via Context-Informed Dynamics Model.

Matthieu Kirchmeyer, Yuan Yin, Jérémie Donà, Nicolas Baskiotis, Alain Rakotomamonjy, Patrick Gallinari

Proceedings of the International Conference on Machine Learning, 2022

Mapping conditional distributions for domain adaptation under generalized target shift.

Matthieu Kirchmeyer, Alain Rakotomamonjy, Emmanuel de Bézenac, Patrick Gallinari

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

Unsupervised domain adaptation with non-stochastic missing data.

Matthieu Kirchmeyer, Patrick Gallinari, Alain Rakotomamonjy, Amin Mantrach

Data Min. Knowl. Discov., 2021

2019

Regression with Conditional GAN.

Karan Aggarwal, Matthieu Kirchmeyer, Pranjul Yadav, S. Sathiya Keerthi, Patrick Gallinari

CoRR, 2019