Austin Stromme

We propose a class of diffusions called Newton-Langevin diffusions and prove that they converge to stationarity exponentially fast with a rate which not only is dimension-free, but also has no dependence on the target distribution. Expand

We develop a framework to derive global rates of convergence for both gradient descent and stochastic gradient descent despite the fact that the barycenter functional is not geodesically convex. Expand

We propose an algebraic framework for generalized graph Laplacians which unifies the study of resistor networks, the critical group, and adjacency matrices. Expand

The frog model is a system of random walks where active particles set sleeping particles in motion. Expand