7 x 3 minutes spotlights
Elsa Cazelles ⋅ Aude Genevay ⋅ Gonzalo Mena ⋅ Christoph Brauer ⋅ Asja Fischer ⋅ Henning Petzka ⋅ Vivien Seguy ⋅ Antoine Rolet ⋅ Sho Sonoda
2017 Poster Spotlights
in
Workshop: Optimal Transport and Machine Learning
in
Workshop: Optimal Transport and Machine Learning
Abstract
- Jérémie Bigot, Elsa Cazelles and Nicolas Papadakis. Central limit theorems for Sinkhorn divergence between probability distributions on finite spaces.
- Aude Genevay. Learning Generative Models with Sinkhorn Divergences
- Gonzalo Mena, David Belanger, Gonzalo Muñoz and Jasper Snoek. Sinkhorn Networks: Using Optimal Transport Techniques to Learn Permutations
- Christoph Brauer, Christian Clason, Dirk Lorenz and Benedikt Wirth. A Sinkhorn-Newton method for entropic optimal transport
- Henning Petzka, Asja Fischer and Denis Lukovnikov. On the regularization of Wasserstein GANs
- Vivien Seguy, Bharath Bhushan Damodaran, Rémi Flamary, Nicolas Courty, Antoine Rolet and Mathieu Blondel. Large Scale Optimal Transport and Mapping Estimation
- Sho Sonoda and Noboru Murata. Transportation analysis of denoising autoencoders: a novel method for analyzing deep neural networks
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