M. Geiger

activity

20182022

most citedSE(3)-equivariant prediction of molecular wavefunctions and electronic densities

25 citations · 34 across the 3 of their papers we have counts for

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2 papers · 1 filter

stat.ML2019

Asymptotic learning curves of kernel methods: empirical data v.s. Teacher-Student paradigm

Stefano Spigler, Mario Geiger, Matthieu Wyart

How many training data are needed to learn a supervised task? It is often observed that the generalization error decreases as $n^{- β}$ where $n$ is the number of training examples…

stat.ML2018

Comparing Dynamics: Deep Neural Networks versus Glassy Systems

M. Baity-Jesi, L. Sagun, M. Geiger +6

We analyze numerically the training dynamics of deep neural networks (DNN) by using methods developed in statistical physics of glassy systems. The two main issues we address are (…