71 citations · 249 across the 16 of their papers we have counts for
6 papers · 1 filter
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…
Invariant Causal Mechanisms through Distribution Matching
Mathieu Chevalley, Charlotte Bunne, Andreas Krause +1
Learning representations that capture the underlying data generating process is a key problem for data efficient and robust use of neural networks. One key property for robustness…
Supervised Training of Conditional Monge Maps
Charlotte Bunne, Andreas Krause, Marco Cuturi
Optimal transport (OT) theory describes general principles to define and select, among many possible choices, the most efficient way to map a probability measure onto another. That…
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 -…
The Schrödinger Bridge between Gaussian Measures has a Closed Form
Charlotte Bunne, Ya-Ping Hsieh, Marco Cuturi +1
The static optimal transport problem between Gaussians seeks to recover an optimal map, or more generally a coupling, to morph a Gaussian into another. It has been…
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…