I'm a PhD student at the University of Geneva under the supervision of François Fleuret. My main interests are generative models, geometric methods, and the utilization of machine learning in scientific applications.

I spent the summer of 2023 interning in the Electronic Structure team of the AI4Science group of Microsoft Research in Amsterdam, and I am currently visiting the group of Tristan Bereau at the University of Heidelberg.

Prior to starting my PhD, I completed a Master's degree in mathematical physics at the University of Hamburg, where my focus was on differential geometry and its connections to various areas of mathematics and physics.

Selected Papers
Multi-Lattice Sampling of Quantum Field Theories via Neural Operator-based Flows
2024
B. Máté and F. Fleuret
ICLR 2024 Workshop on AI4DifferentialEquations in Science
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Learning Interpolations between Boltzmann Densities
2023
B. Máté and F. Fleuret
Transactions on Machine Learning Research (TMLR)
paper | code | summary | bib
Flowification: Everything is a Normalizing flow
2022
B. Máté*, S. Klein*, T. Golling, F. Fleuret
Neural Information Processing Systems (NeurIPS)
paper | code | summary | bib
Deformations of Boltzmann Distributions
2022
B. Máté and F. Fleuret
NeurIPS 2022 Workshop on ML4Physics
paper | summary | bib