Interpolating between Optimal Transport and MMD using Sinkhorn Divergences

18 October 2018

Jean Feydy

Thibault Séjourné

François-Xavier Vialard

Papers citing "Interpolating between Optimal Transport and MMD using Sinkhorn Divergences"

39 / 89 papers shown

Title
BITES: Balanced Individual Treatment Effect for Survival data Stefan Schrod Andreas Schäfer S. Solbrig R. Lohmayer W. Gronwald P. Oefner T. Beissbarth Rainer Spang H. Zacharias Michael Altenbuchinger CML 15 22 0 05 Jan 2022
Manipulation of Granular Materials by Learning Particle Interactions Neea Tuomainen David Blanco Mulero Ville Kyrki 11 20 0 03 Nov 2021
Understanding Entropic Regularization in GANs Daria Reshetova Yikun Bai Xiugang Wu Ayfer Özgür 8 7 0 02 Nov 2021
Don't Generate Me: Training Differentially Private Generative Models with Sinkhorn Divergence Tianshi Cao Alex Bie Arash Vahdat Sanja Fidler Karsten Kreis SyDa DiffM 13 71 0 01 Nov 2021
Hamiltonian Monte Carlo with Asymmetrical Momentum Distributions Soumyadip Ghosh Ying-Ling Lu Aditya Gopalan 17 3 0 21 Oct 2021
Order Constraints in Optimal Transport Fabian Lim L. Wynter Shiau Hong Lim OT 31 4 0 14 Oct 2021
Adversarial examples by perturbing high-level features in intermediate decoder layers Vojtěch Čermák Lukáš Adam AAML GAN 35 0 0 14 Oct 2021
Challenges for Unsupervised Anomaly Detection in Particle Physics Katherine Fraser S. Homiller Rashmish K. Mishra B. Ostdiek M. Schwartz DRL 27 43 0 13 Oct 2021
KNOT: Knowledge Distillation using Optimal Transport for Solving NLP Tasks Rishabh Bhardwaj Tushar Vaidya Soujanya Poria OT FedML 65 7 0 06 Oct 2021
Top-N: Equivariant set and graph generation without exchangeability Clément Vignac P. Frossard BDL 71 34 0 05 Oct 2021
Factored couplings in multi-marginal optimal transport via difference of convex programming Q. Tran H. Janati I. Redko Rémi Flamary Nicolas Courty OT 35 1 0 01 Oct 2021
Optimal transport weights for causal inference Eric A. Dunipace CML OT 28 9 0 05 Sep 2021
Fast and Scalable Optimal Transport for Brain Tractograms Jean Feydy Pierre Roussillon A. Trouvé Pietro Gori OT 19 24 0 05 Jul 2021
Discrepancy-based Inference for Intractable Generative Models using Quasi-Monte Carlo Ziang Niu J. Meier F. Briol 24 12 0 22 Jun 2021
KALE Flow: A Relaxed KL Gradient Flow for Probabilities with Disjoint Support Pierre Glaser Michael Arbel A. Gretton 44 37 0 16 Jun 2021
PriorGrad: Improving Conditional Denoising Diffusion Models with Data-Dependent Adaptive Prior Sang-gil Lee Heeseung Kim Chaehun Shin Xu Tan Chang-Shu Liu Qi Meng Tao Qin Wei Chen Sung-Hoon Yoon Tie-Yan Liu DiffM 23 81 0 11 Jun 2021
Proximal Optimal Transport Modeling of Population Dynamics Charlotte Bunne Laetitia Meng-Papaxanthos Andreas Krause Marco Cuturi OT 45 81 0 11 Jun 2021
A Neural Tangent Kernel Perspective of GANs Jean-Yves Franceschi Emmanuel de Bézenac Ibrahim Ayed Mickaël Chen Sylvain Lamprier Patrick Gallinari 31 26 0 10 Jun 2021
Solving Schrödinger Bridges via Maximum Likelihood Francisco Vargas Pierre Thodoroff Neil D. Lawrence A. Lamacraft OT 26 131 0 03 Jun 2021
Optimizing Functionals on the Space of Probabilities with Input Convex Neural Networks David Alvarez-Melis Yair Schiff Youssef Mroueh 40 52 0 01 Jun 2021
Unbalanced minibatch Optimal Transport; applications to Domain Adaptation Kilian Fatras Thibault Séjourné Nicolas Courty Rémi Flamary OT 37 146 0 05 Mar 2021
Wasserstein GANs Work Because They Fail (to Approximate the Wasserstein Distance) Jan Stanczuk Christian Etmann L. Kreusser Carola-Bibiane Schönlieb GAN 16 48 0 02 Mar 2021
Differentiable Particle Filtering via Entropy-Regularized Optimal Transport Adrien Corenflos James Thornton George Deligiannidis Arnaud Doucet OT 41 66 0 15 Feb 2021
Smooth $p$ -Wasserstein Distance: Structure, Empirical Approximation, and Statistical Applications Sloan Nietert Ziv Goldfeld Kengo Kato 34 30 0 11 Jan 2021
Minibatch optimal transport distances; analysis and applications Kilian Fatras Younes Zine Szymon Majewski Rémi Flamary Rémi Gribonval Nicolas Courty OT 66 53 0 05 Jan 2021
Convergence and finite sample approximations of entropic regularized Wasserstein distances in Gaussian and RKHS settings M. H. Quang 54 5 0 05 Jan 2021
Permutation invariant networks to learn Wasserstein metrics Arijit Sehanobish N. Ravindra David van Dijk OOD 17 2 0 12 Oct 2020
The Unbalanced Gromov Wasserstein Distance: Conic Formulation and Relaxation Thibault Séjourné François-Xavier Vialard Gabriel Peyré OT 22 67 0 09 Sep 2020
End-to-end Sinkhorn Autoencoder with Noise Generator Kamil Deja Jan Dubiñski Piotr W. Nowak S. Wenzel Tomasz Trzciñski SyDa 22 22 0 11 Jun 2020
Statistical and Topological Properties of Sliced Probability Divergences Kimia Nadjahi Alain Durmus Lénaïc Chizat Soheil Kolouri Shahin Shahrampour Umut Simsekli 26 80 0 12 Mar 2020
Regularized Optimal Transport is Ground Cost Adversarial Franccois-Pierre Paty Marco Cuturi OT AAML OOD 25 29 0 10 Feb 2020
Geometric Dataset Distances via Optimal Transport David Alvarez-Melis Nicolò Fusi OT 72 194 0 07 Feb 2020
Gaussian-Smooth Optimal Transport: Metric Structure and Statistical Efficiency Ziv Goldfeld Kristjan Greenewald OT 17 39 0 24 Jan 2020
Sinkhorn Divergences for Unbalanced Optimal Transport Thibault Séjourné Jean Feydy Franccois-Xavier Vialard A. Trouvé Gabriel Peyré OT 22 71 0 28 Oct 2019
How Well Do WGANs Estimate the Wasserstein Metric? Anton Mallasto Guido Montúfar Augusto Gerolin 22 25 0 09 Oct 2019
Flat Metric Minimization with Applications in Generative Modeling Thomas Möllenhoff Daniel Cremers 17 5 0 12 May 2019
The Born Supremacy: Quantum Advantage and Training of an Ising Born Machine Brian Coyle Daniel Mills V. Danos E. Kashefi 27 155 0 03 Apr 2019
Wasserstein Barycenter Model Ensembling Pierre L. Dognin Igor Melnyk Youssef Mroueh Jerret Ross Cicero Nogueira dos Santos Tom Sercu 24 24 0 13 Feb 2019
Differential Properties of Sinkhorn Approximation for Learning with Wasserstein Distance Giulia Luise Alessandro Rudi Massimiliano Pontil C. Ciliberto OT 24 130 0 30 May 2018