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"

50 / 310 papers shown

Title
Lower Complexity Adaptation for Empirical Entropic Optimal Transport Michel Groppe Shayan Hundrieser OT 62 11 0 23 Jun 2023
Learning Elastic Costs to Shape Monge Displacements Michal Klein Aram-Alexandre Pooladian Pierre Ablin Eugène Ndiaye Jonathan Niles-Weed Marco Cuturi 79 4 0 20 Jun 2023
Training generative models from privatized data Daria Reshetova Wei-Ning Chen Ayfer Özgür FedML 60 3 0 15 Jun 2023
Importance Sparsification for Sinkhorn Algorithm Mengyun Li Jun Yu Tao Li Cheng Meng OT 124 8 0 11 Jun 2023
Neural Injective Functions for Multisets, Measures and Graphs via a Finite Witness Theorem Tal Amir S. Gortler Ilai Avni Ravi Ravina Nadav Dym 165 28 0 10 Jun 2023
Training neural operators to preserve invariant measures of chaotic attractors Ruoxi Jiang Peter Y. Lu Elena Orlova Rebecca Willett AI4TS 113 26 0 01 Jun 2023
Bringing regularized optimal transport to lightspeed: a splitting method adapted for GPUs Jacob Lindbäck Zesen Wang Mikael Johansson OT 98 1 0 29 May 2023
Diffeomorphic Mesh Deformation via Efficient Optimal Transport for Cortical Surface Reconstruction Tung Le Khai Nguyen Shanlin Sun Kun Han Nhat Ho Xiaohui Xie 66 5 0 27 May 2023
Exact Generalization Guarantees for (Regularized) Wasserstein Distributionally Robust Models Waïss Azizian F. Iutzeler J. Malick OOD 88 10 0 26 May 2023
Learning to Quantize Vulnerability Patterns and Match to Locate Statement-Level Vulnerabilities Michael Fu Trung Le Van Nguyen Chakkrit Tantithamthavorn Dinh Q. Phung 61 3 0 26 May 2023
Rectifying Group Irregularities in Explanations for Distribution Shift Adam Stein Yinjun Wu Eric Wong Mayur Naik 92 1 0 25 May 2023
Feature-aligned N-BEATS with Sinkhorn divergence Joon-Young Lee Myeongho Jeon Myung-joo Kang Kyung-soon Park AI4TS 57 0 0 24 May 2023
SNEkhorn: Dimension Reduction with Symmetric Entropic Affinities Hugues van Assel Titouan Vayer Rémi Flamary Nicolas Courty 87 9 0 23 May 2023
Parameter-Efficient Learning for Text-to-Speech Accent Adaptation Lijie Yang Chao-Han Huck Yang Jen-Tzung Chien 91 11 0 18 May 2023
Weak Limits for Empirical Entropic Optimal Transport: Beyond Smooth Costs Alberto González Sanz Shayan Hundrieser OT 48 11 0 16 May 2023
Reconstructing Animatable Categories from Videos Gengshan Yang Chaoyang Wang Dinesh Reddy Narapureddy Deva Ramanan 104 37 0 10 May 2023
Scalable Optimal Transport Methods in Machine Learning: A Contemporary Survey Abdelwahed Khamis Russell Tsuchida Mohamed Tarek V. Rolland Lars Petersson OT 139 14 0 08 May 2023
LAVA: Data Valuation without Pre-Specified Learning Algorithms H. Just Feiyang Kang Jiachen T. Wang Yi Zeng Myeongseob Ko Ming Jin R. Jia 111 62 0 28 Apr 2023
Energy-Based Sliced Wasserstein Distance Khai Nguyen Nhat Ho 83 23 0 26 Apr 2023
ProPanDL: A Modular Architecture for Uncertainty-Aware Panoptic Segmentation Jacob Deery Chang Won Lee Steven Waslander 56 2 0 17 Apr 2023
Beyond NeRF Underwater: Learning Neural Reflectance Fields for True Color Correction of Marine Imagery Tianyi Zhang Matthew Johnson-Roberson 93 26 0 06 Apr 2023
Dynamic Point Fields Sergey Prokudin Qianli Ma Maxime Raafat Julien P. C. Valentin Siyu Tang 3DH AI4CE 113 28 0 05 Apr 2023
kNN-Res: Residual Neural Network with kNN-Graph coherence for point cloud registration Muhammad S. Battikh D. Hammill Mat Cook Artem Lenskiy 3DPC 18 1 0 31 Mar 2023
On the Effect of Initialization: The Scaling Path of 2-Layer Neural Networks Sebastian Neumayer Lénaïc Chizat M. Unser 65 2 0 31 Mar 2023
Achieving Counterfactual Fairness with Imperfect Structural Causal Model Tri Dung Duong Qian Li Guandong Xu 56 2 0 26 Mar 2023
Wasserstein Loss for Semantic Editing in the Latent Space of GANs Perla Doubinsky Nicolas Audebert M. Crucianu Hervé Le Borgne GAN 38 1 0 22 Mar 2023
Doubly Regularized Entropic Wasserstein Barycenters Lénaïc Chizat 77 14 0 21 Mar 2023
Uncovering Challenges of Solving the Continuous Gromov-Wasserstein Problem Xavier Aramayo Carrasco Maksim Nekrashevich Petr Mokrov Evgeny Burnaev Alexander Korotin OT 106 7 0 10 Mar 2023
How optimal transport can tackle gender biases in multi-class neural-network classifiers for job recommendations? Fanny Jourdan Titon Tshiongo Kaninku Nicholas M. Asher Jean-Michel Loubes Laurent Risser FaML 74 4 0 27 Feb 2023
Heterogeneous Neuronal and Synaptic Dynamics for Spike-Efficient Unsupervised Learning: Theory and Design Principles Biswadeep Chakraborty Saibal Mukhopadhyay 88 10 0 22 Feb 2023
Transformed Distribution Matching for Missing Value Imputation He Zhao Ke Sun Amir Dezfouli Edwin V. Bonilla 94 21 0 20 Feb 2023
An overview of differentiable particle filters for data-adaptive sequential Bayesian inference Xiongjie Chen Yunpeng Li 82 16 0 19 Feb 2023
Distances for Markov Chains, and Their Differentiation Tristan Brugere Qingsong Wang Yusu Wang OT OOD 60 4 0 16 Feb 2023
On Rank Energy Statistics via Optimal Transport: Continuity, Convergence, and Change Point Detection Matthew Werenski Shoaib Bin Masud James M. Murphy Shuchin Aeron 72 4 0 15 Feb 2023
The Monge Gap: A Regularizer to Learn All Transport Maps Théo Uscidda Marco Cuturi OT 96 30 0 09 Feb 2023
Monge, Bregman and Occam: Interpretable Optimal Transport in High-Dimensions with Feature-Sparse Maps Marco Cuturi Michal Klein Pierre Ablin OT 86 15 0 08 Feb 2023
Domain Adaptation for Time Series Under Feature and Label Shifts Huan He Owen Queen Teddy Koker Consuelo Cuevas Theodoros Tsiligkaridis Marinka Zitnik AI4TS 112 71 0 06 Feb 2023
Self-Consistent Velocity Matching of Probability Flows Lingxiao Li Samuel Hurault Justin Solomon 108 15 0 31 Jan 2023
Fast Computation of Optimal Transport via Entropy-Regularized Extragradient Methods Gen Li Yanxi Chen Yu Huang Yuejie Chi H. Vincent Poor Yuxin Chen OT 80 5 0 30 Jan 2023
Pre-training for Speech Translation: CTC Meets Optimal Transport Hang Le Hongyu Gong Changhan Wang J. Pino Benjamin Lecouteux D. Schwab OT 102 26 0 27 Jan 2023
Maximum Mean Discrepancy Kernels for Predictive and Prognostic Modeling of Whole Slide Images Piotr Keller Muhammad Dawood F. Minhas 49 3 0 23 Jan 2023
Simplex Autoencoders Aymene Mohammed Bouayed D. Naccache SyDa 55 0 0 16 Jan 2023
Markovian Sliced Wasserstein Distances: Beyond Independent Projections Khai Nguyen Zhaolin Ren Nhat Ho 78 8 0 10 Jan 2023
Modeling Multimodal Aleatoric Uncertainty in Segmentation with Mixture of Stochastic Experts Zhitong Gao Yucong Chen Chuyu Zhang Xuming He UQCV 57 5 0 14 Dec 2022
Estimating Regression Predictive Distributions with Sample Networks Ali Harakeh Jordan S. K. Hu Naiqing Guan Steven L. Waslander Liam Paull BDL UQCV 44 4 0 24 Nov 2022
Representational dissimilarity metric spaces for stochastic neural networks Lyndon Duong Jingyang Zhou Josue Nassar Jules Berman Jeroen Olieslagers Alex H. Williams 79 22 0 21 Nov 2022
Unbalanced Optimal Transport, from Theory to Numerics Thibault Séjourné Gabriel Peyré Franccois-Xavier Vialard OT 104 49 0 16 Nov 2022
Cluster-Based Autoencoders for Volumetric Point Clouds Stephan Antholzer Martin Berger Tobias Hell 3DPC 14 0 0 02 Nov 2022
BSDF Importance Baking: A Lightweight Neural Solution to Importance Sampling General Parametric BSDFs Yaoyi Bai Songyin Wu Z. Zeng Beibei Wang Ling-Qi Yan 60 2 0 25 Oct 2022
Budget-Constrained Bounds for Mini-Batch Estimation of Optimal Transport David Alvarez-Melis Nicolò Fusi Lester W. Mackey Tal Wagner OT 98 1 0 24 Oct 2022