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Learning Generative Models with Sinkhorn Divergences

1 June 2017

Papers citing "Learning Generative Models with Sinkhorn Divergences"

50 / 382 papers shown

Title
OTFace: Hard Samples Guided Optimal Transport Loss for Deep Face Representation J. Qian Shumin Zhu Chao-Yue Zhao Jian Yang Wai Keung Wong CVBM 60 5 0 28 Mar 2022
Wasserstein Distributionally Robust Optimization with Wasserstein Barycenters Tim Tsz-Kit Lau Han Liu OOD 91 2 0 23 Mar 2022
SiMCa: Sinkhorn Matrix Factorization with Capacity Constraints Eric Daoud Luca Ganassali Antoine Baker Marc Lelarge 56 0 0 18 Mar 2022
Adversarial Support Alignment Shangyuan Tong T. Garipov Yang Zhang Shiyu Chang Tommi Jaakkola 63 10 0 16 Mar 2022
Interpretable Dysarthric Speaker Adaptation based on Optimal-Transport Rosanna Turrisi Leonardo Badino 41 3 0 14 Mar 2022
Partial Wasserstein Adversarial Network for Non-rigid Point Set Registration Zifeng Wang Nan Xue Ling Lei Guisong Xia 3DPC 60 4 0 04 Mar 2022
Debiaser Beware: Pitfalls of Centering Regularized Transport Maps Aram-Alexandre Pooladian Marco Cuturi Jonathan Niles-Weed OT 66 16 0 17 Feb 2022
Online Learning to Transport via the Minimal Selection Principle Wenxuan Guo Y. Hur Tengyuan Liang Christopher Ryan 55 3 0 09 Feb 2022
Optimal Transport of Classifiers to Fairness Maarten Buyl T. D. Bie FaML 54 11 0 08 Feb 2022
On Unbalanced Optimal Transport: Gradient Methods, Sparsity and Approximation Error Quang Minh Nguyen Hoang H. Nguyen Yi Zhou Lam M. Nguyen OT 65 11 0 08 Feb 2022
Distributional Reinforcement Learning by Sinkhorn Divergence Ke Sun Yingnan Zhao Wulong Liu Bei Jiang Linglong Kong 78 0 0 01 Feb 2022
Riemannian block SPD coupling manifold and its application to optimal transport Andi Han Bamdev Mishra Pratik Jawanpuria Junbin Gao OT 81 6 0 30 Jan 2022
Wassersplines for Neural Vector Field--Controlled Animation Paul Zhang Dmitriy Smirnov Justin Solomon 68 4 0 28 Jan 2022
Optimal transport for causal discovery Ruibo Tu Kun Zhang Hedvig Kjellström Cheng Zhang 140 20 0 23 Jan 2022
An Homogeneous Unbalanced Regularized Optimal Transport model with applications to Optimal Transport with Boundary Théo Lacombe OT 30 3 0 06 Jan 2022
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 58 23 0 05 Jan 2022
Learning to Generate Novel Classes for Deep Metric Learning Kyungmoo Lee Sungyeon Kim Seunghoon Hong Suha Kwak 85 1 0 04 Jan 2022
Entropy Regularized Optimal Transport Independence Criterion Lang Liu Soumik Pal Zaïd Harchaoui OT 77 14 0 31 Dec 2021
Computing Divergences between Discrete Decomposable Models Loong Kuan Lee Nico Piatkowski Franccois Petitjean Geoffrey I. Webb 27 2 0 08 Dec 2021
Music-to-Dance Generation with Optimal Transport Shuang Wu Shijian Lu Li Cheng OT 70 3 0 03 Dec 2021
A new Sinkhorn algorithm with Deletion and Insertion operations Luc Brun Benoit Gaüzère Sébastien Bougleux Florian Yger 22 1 0 29 Nov 2021
Randomized Stochastic Gradient Descent Ascent Othmane Sebbouh Marco Cuturi Gabriel Peyré 440 7 0 25 Nov 2021
Input Convex Gradient Networks Jack Richter-Powell Jonathan Lorraine Brandon Amos 74 15 0 23 Nov 2021
Understanding Entropic Regularization in GANs Daria Reshetova Yikun Bai Xiugang Wu Ayfer Özgür 72 7 0 02 Nov 2021
Nearly Tight Convergence Bounds for Semi-discrete Entropic Optimal Transport Shin Kamada 80 15 0 25 Oct 2021
Statistical and Topological Properties of Gaussian Smoothed Sliced Probability Divergences A. Rakotomamonjy Mokhtar Z. Alaya Maxime Bérar Gilles Gasso 103 5 0 20 Oct 2021
Generative Modeling with Optimal Transport Maps Litu Rout Alexander Korotin Evgeny Burnaev OT DiffM 197 70 0 06 Oct 2021
SPATE-GAN: Improved Generative Modeling of Dynamic Spatio-Temporal Patterns with an Autoregressive Embedding Loss Konstantin Klemmer Tianlin Xu Beatrice Acciaio Daniel B. Neill AI4TS 113 14 0 30 Sep 2021
Reversible Gromov-Monge Sampler for Simulation-Based Inference Y. Hur Wenxuan Guo Tengyuan Liang 94 9 0 28 Sep 2021
Entropic estimation of optimal transport maps Aram-Alexandre Pooladian Jonathan Niles-Weed OT 122 108 0 24 Sep 2021
Sinkhorn Distributionally Robust Optimization Jie Wang Rui Gao Yao Xie 151 40 0 24 Sep 2021
Optimal transport weights for causal inference Eric A. Dunipace CML OT 68 9 0 05 Sep 2021
Entropic Gromov-Wasserstein between Gaussian Distributions Khang Le Dung D. Le Huy Nguyen Dat Do Tung Pham Nhat Ho OT 79 18 0 24 Aug 2021
Embedding Signals on Knowledge Graphs with Unbalanced Diffusion Earth Mover's Distance Alexander Tong G. Huguet Dennis L. Shung A. Natik Manik Kuchroo Guillaume Lajoie Guy Wolf Smita Krishnaswamy 83 6 0 26 Jul 2021
AASAE: Augmentation-Augmented Stochastic Autoencoders William Falcon A. Jha Teddy Koker Kyunghyun Cho 102 0 0 26 Jul 2021
Optimal transport-based machine learning to match specific patterns: application to the detection of molecular regulation patterns in omics data T. Nguyen Warith Harchaoui Lucile Mégret Cloé Mendoza Olivier Bouaziz C. Néri Antoine Chambaz 34 1 0 21 Jul 2021
Scalable Optimal Transport in High Dimensions for Graph Distances, Embedding Alignment, and More Johannes Klicpera Marten Lienen Stephan Günnemann OT 81 13 0 14 Jul 2021
Hidden Convexity of Wasserstein GANs: Interpretable Generative Models with Closed-Form Solutions Arda Sahiner Tolga Ergen Batu Mehmet Ozturkler Burak Bartan John M. Pauly Morteza Mardani Mert Pilanci GAN 95 20 0 12 Jul 2021
A stochastic Gauss-Newton algorithm for regularized semi-discrete optimal transport Bernard Bercu Jérémie Bigot S. Gadat Emilia Siviero 106 6 0 12 Jul 2021
Direct Measure Matching for Crowd Counting Hui Lin Xiaopeng Hong Zhiheng Ma Xing Wei Yunfeng Qiu Yaowei Wang Yihong Gong OT 75 45 0 04 Jul 2021
Deep Inertial Navigation using Continuous Domain Adaptation and Optimal Transport Mohammed Alloulah Maximilian Arnold Anton Isopoussu OOD 63 2 0 29 Jun 2021
Asymptotics for semi-discrete entropic optimal transport Jason M. Altschuler Jonathan Niles-Weed Austin J. Stromme 44 27 0 22 Jun 2021
Discrepancy-based Inference for Intractable Generative Models using Quasi-Monte Carlo Ziang Niu J. Meier F. Briol 106 13 0 22 Jun 2021
Manifold Matching via Deep Metric Learning for Generative Modeling Mengyu Dai Haibin Hang GAN 43 10 0 20 Jun 2021
KALE Flow: A Relaxed KL Gradient Flow for Probabilities with Disjoint Support Pierre Glaser Michael Arbel Arthur Gretton 131 40 0 16 Jun 2021
Non-asymptotic convergence bounds for Wasserstein approximation using point clouds Q. Mérigot F. Santambrogio Clément Sarrazin 48 28 0 15 Jun 2021
Learning Revenue-Maximizing Auctions With Differentiable Matching Michael J. Curry Uro Lyi Tom Goldstein John P. Dickerson 46 20 0 15 Jun 2021
A Wasserstein Minimax Framework for Mixed Linear Regression Theo Diamandis Yonina C. Eldar Alireza Fallah Farzan Farnia Asuman Ozdaglar 73 7 0 14 Jun 2021
Separation Results between Fixed-Kernel and Feature-Learning Probability Metrics Carles Domingo-Enrich Youssef Mroueh 66 1 0 10 Jun 2021
Conditional COT-GAN for Video Prediction with Kernel Smoothing Tianlin Xu Beatrice Acciaio GAN AI4TS CML 33 5 0 10 Jun 2021