Mario Geiger

Scaling description of generalization with number of parameters in deep learning

2020 · Journal of Statistical Mechanics Theory and Experiment

Abstract Supervised deep learning involves the training of neural networks with a large number N of parameters. For large enough N , in the so-called over-parametrized regime, one can essentially fit the training data points. …

EquiJump: Protein Dynamics Simulation via SO(3)-Equivariant Stochastic Interpolants

2024 · arXiv (Cornell University)

Mapping the conformational dynamics of proteins is crucial for elucidating their functional mechanisms. While Molecular Dynamics (MD) simulation enables detailed time evolution of protein motion, its computational toll hinders its use in practice. To address …