125 citations · 859 across the 68 of their papers we have counts for
4 papers · 1 filter
Singular-limit analysis of gradient descent with noise injection
Anna Shalova, André Schlichting, Mark Peletier
We study the limiting dynamics of a large class of noisy gradient descent systems in the overparameterized regime. In this regime the set of global minimizers of the loss is large,…
Neural Langevin Dynamics: towards interpretable Neural Stochastic Differential Equations
Simon M. Koop, Mark A. Peletier, Jacobus W. Portegies +1
Neural Stochastic Differential Equations (NSDE) have been trained as both Variational Autoencoders, and as GANs. However, the resulting Stochastic Differential Equations can be har…
Universal Approximation in Dropout Neural Networks
Oxana A. Manita, Mark A. Peletier, Jacobus W. Portegies +2
We prove two universal approximation theorems for a range of dropout neural networks. These are feed-forward neural networks in which each edge is given a random -valued f…
SciSports: Learning football kinematics through two-dimensional tracking data
Anatoliy Babic, Harshit Bansal, Gianluca Finocchio +7
SciSports is a Dutch startup company specializing in football analytics. This paper describes a joint research effort with SciSports, during the Study Group Mathematics with Indust…