1 citations · 1 across the 5 of their papers we have counts for
5 papers
Diffeomorphic Optimization
Ludwig Winkler, Andrew Leaver-Fay, Joseph Kleinhenz +1
Generative models learn data distributions that reside on a low-dimensional manifold within a higher-dimensional ambient space. Optimizing differentiable objectives on this manifol…
Enhanced Diffusion Sampling: Efficient Rare Event Sampling and Free Energy Calculation with Diffusion Models
Yu Xie, Ludwig Winkler, Lixin Sun +10
The rare-event sampling problem has long been the central limiting factor in molecular dynamics (MD), especially in biomolecular simulation. Recently, diffusion models such as BioE…
Time-Reversible Bridges of Data with Machine Learning
Ludwig Winkler
The analysis of dynamical systems is a fundamental tool in the natural sciences and engineering. It is used to understand the evolution of systems as large as entire galaxies and a…
Bridging discrete and continuous state spaces: Exploring the Ehrenfest process in time-continuous diffusion models
Ludwig Winkler, Lorenz Richter, Manfred Opper
Generative modeling via stochastic processes has led to remarkable empirical results as well as to recent advances in their theoretical understanding. In principle, both space and…
Fast and Unified Path Gradient Estimators for Normalizing Flows
Lorenz Vaitl, Ludwig Winkler, Lorenz Richter +1
Recent work shows that path gradient estimators for normalizing flows have lower variance compared to standard estimators for variational inference, resulting in improved training.…