Matthieu Kirchmeyer

I am a senior ML Scientist at Genentech in the Prescient Design team in New York, USA. I am developping ML generative and predictive models for molecular design.

I obtained a PhD degree at Sorbonne Université. My PhD research focused on improving out-of-distribution generalization of deep learning models in the setting of classification and physical dynamics modelling. I obtained a Master's degree at Mines Paris - PSL and at Ecole Normale Supérieure Paris Saclay (Master MVA).

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Publications

	Score-based 3D molecule generation with neural fields M. Kirchmeyer, P. O. Pinheiro, S. Saremi NeurIPS 2024 ArXiv / OpenReview / code /
	Lab-in-the-loop therapeutic antibody design with deep learning N. Frey, I. Hötzel, S. Stanton, R. Kelly, R. Alberstein, ..., M. Kirchmeyer, ..., V. Gligorijevic. BioRxiv* ArXiv /
	Antibody DomainBed: Out-of-Distribution Generalization in Therapeutic Protein Design N. Tagasovka, J. Park, M. Kirchmeyer, ..., K. Cho ArXiv ArXiv / code /
	Continuous PDE Dynamics Forecasting with Implicit Neural Representations Y. Yin, M. Kirchmeyer, J-Y. Franceschi, A. Rakotomamonjy, P. Gallinari ICLR 2023 - Spotlight* (notable-top-25%) arXiv / OpenReview / code /
	Diverse Weight Averaging for Out-of-Distribution Generalization A. Ramé, M. Kirchmeyer, T. Rahier, A. Rakotomamonjy, P. Gallinari, M. Cord NeurIPS 2022 arXiv / OpenReview / code / slides / poster
	Generalizing to New Physical Systems via Context-Informed Dynamics Model M. Kirchmeyer, Y. Yin, J. Donà, N. Baskiotis, A. Rakotomamonjy, P. Gallinari ICML 2022 arXiv / PMLR / code / slides / poster / video
	Mapping conditional distributions for domain adaptation under generalized target shift M. Kirchmeyer, A. Rakotomamonjy, E. de Bézenac, P. Gallinari ICLR 2022 arXiv / OpenReview / code / slides / poster / video

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