Matthieu Kirchmeyer

I am a senior ML Scientist at Genentech in the Prescient Design team. 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
PontTuset Score-based 3D molecule generation with neural fields
M. Kirchmeyer*, P. O. Pinheiro*, S. Saremi (*equal contribution)
NeurIPS 2024
ArXiv / OpenReview / code /

PontTuset Antibody DomainBed: Out-of-Distribution Generalization in Therapeutic Protein Design
N. Tagasovka, J. Park, M. Kirchmeyer, ..., K. Cho
Under Review
ArXiv / code /

PontTuset Continuous PDE Dynamics Forecasting with Implicit Neural Representations
Y. Yin*, M. Kirchmeyer*, J-Y. Franceschi*, A. Rakotomamonjy, P. Gallinari (*equal contribution)
ICLR 2023 - Spotlight (notable-top-25%). Preliminary version at NeurIPS 2022 AI4Science Workshop, ICLR 2023 Neural Fields Workshop.
arXiv / OpenReview / code /

PontTuset Diverse Weight Averaging for Out-of-Distribution Generalization
A. Ramé*, M. Kirchmeyer*, T. Rahier, A. Rakotomamonjy, P. Gallinari, M. Cord (*equal contribution)
NeurIPS 2022. Preliminary version at ICML 2022 PODS Workshop
arXiv / OpenReview / code / slides / poster

PontTuset Generalizing to New Physical Systems via Context-Informed Dynamics Model
M. Kirchmeyer*, Y. Yin*, J. DonĂ , N. Baskiotis, A. Rakotomamonjy, P. Gallinari (*equal contribution)
ICML 2022
arXiv / PMLR / code / slides / poster / video

PontTuset Mapping conditional distributions for domain adaptation under generalized target shift
M. Kirchmeyer, A. Rakotomamonjy, E. de BĂ©zenac, P. Gallinari
ICLR 2022. Also presented at CAp 2022 (oral)
arXiv / OpenReview / code / slides / poster / video

PontTuset Unsupervised domain adaptation with non-stochastic missing data
M. Kirchmeyer, P. Gallinari, A. Rakotomamonjy, A. Mantrach
ECML-PKDD 2021 - Data Mining and Knowledge Discovery journal.
arXiv / journal link / pdf / code / slides

Older
PontTuset Conformal Robotic Stereolithography
A. Stevens*, R. Oliver*, M. Kirchmeyer, J. Wu, L. Chin, E. Polsen, C. Archer, C. Boyle, J. Garber and J. Hart (*equal contribution)
3D Printing and Additive Manufacturing journal, 2016.
journal link


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