3 papers
cs.AI2024
Growing Tiny Networks: Spotting Expressivity Bottlenecks and Fixing Them Optimally
Manon Verbockhaven, Sylvain Chevallier, Guillaume Charpiat +1
Machine learning tasks are generally formulated as optimization problems, where one searches for an optimal function within a certain functional space. In practice, parameterized f…
cs.AI2024
Time and State Dependent Neural Delay Differential Equations
Thibault Monsel, Onofrio Semeraro, Lionel Mathelin +1
Discontinuities and delayed terms are encountered in the governing equations of a large class of problems ranging from physics and engineering to medicine and economics. These syst…
cond-mat.soft2024
Rotation-equivariant Graph Neural Networks for Learning Glassy Liquids Representations
Francesco Saverio Pezzicoli, Guillaume Charpiat, François P. Landes
The difficult problem of relating the static structure of glassy liquids and their dynamics is a good target for Machine Learning, an approach which excels at finding complex patte…