most citedLearning Generative Models across Incomparable Spaces

25 citations · 68 across the 4 of their papers we have counts for

collaborators

5 papers

cs.LG20231 cited

Unbalanced Diffusion Schrödinger Bridge

Matteo Pariset, Ya-Ping Hsieh, Charlotte Bunne +2

Schrödinger bridges (SBs) provide an elegant framework for modeling the temporal evolution of populations in physical, chemical, or biological systems. Such natural processes are c…

cs.LG20221 cited

Neural Unbalanced Optimal Transport via Cycle-Consistent Semi-Couplings

Frederike Lübeck, Charlotte Bunne, Gabriele Gut +3

Comparing unpaired samples of a distribution or population taken at different points in time is a fundamental task in many application domains where measuring populations is destru…

cs.LG202222 cited

Multi-Scale Representation Learning on Proteins

Vignesh Ram Somnath, Charlotte Bunne, Andreas Krause

Proteins are fundamental biological entities mediating key roles in cellular function and disease. This paper introduces a multi-scale graph construction of a protein -- HoloProt -…

cs.LG202220 cited

Optimal Transport Tools (OTT): A JAX Toolbox for all things Wasserstein

Marco Cuturi, Laetitia Meng-Papaxanthos, Yingtao Tian +3

Optimal transport tools (OTT-JAX) is a Python toolbox that can solve optimal transport problems between point clouds and histograms. The toolbox builds on various JAX features, suc…

cs.LG201925 cited

Learning Generative Models across Incomparable Spaces

Charlotte Bunne, David Alvarez-Melis, Andreas Krause +1

Generative Adversarial Networks have shown remarkable success in learning a distribution that faithfully recovers a reference distribution in its entirety. However, in some cases,…