Learning Generative Models with Sinkhorn Divergences

1 June 2017

Papers citing "Learning Generative Models with Sinkhorn Divergences"

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Title
Online Learning to Transport via the Minimal Selection Principle Wenxuan Guo Y. Hur Tengyuan Liang Christopher Ryan 11 3 0 09 Feb 2022
Optimal Transport of Classifiers to Fairness Maarten Buyl T. D. Bie FaML 11 9 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 18 11 0 08 Feb 2022
Distributional Reinforcement Learning by Sinkhorn Divergence Ke Sun Yingnan Zhao Wulong Liu Bei Jiang Linglong Kong 17 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 10 6 0 30 Jan 2022
Wassersplines for Neural Vector Field--Controlled Animation Paul Zhang Dmitriy Smirnov Justin Solomon 14 4 0 28 Jan 2022
Optimal transport for causal discovery Ruibo Tu Kun Zhang Hedvig Kjellström Cheng Zhang 95 19 0 23 Jan 2022
An Homogeneous Unbalanced Regularized Optimal Transport model with applications to Optimal Transport with Boundary Théo Lacombe OT 11 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 15 22 0 05 Jan 2022
Learning to Generate Novel Classes for Deep Metric Learning Kyungmoo Lee Sungyeon Kim Seunghoon Hong Suha Kwak 8 1 0 04 Jan 2022
Entropy Regularized Optimal Transport Independence Criterion Lang Liu Soumik Pal Zaïd Harchaoui OT 15 12 0 31 Dec 2021
Computing Divergences between Discrete Decomposable Models Loong Kuan Lee Nico Piatkowski Franccois Petitjean Geoffrey I. Webb 8 2 0 08 Dec 2021
Music-to-Dance Generation with Optimal Transport Shuang Wu Shijian Lu Li Cheng OT 19 3 0 03 Dec 2021
A new Sinkhorn algorithm with Deletion and Insertion operations Luc Brun Benoit Gaüzère Sébastien Bougleux Florian Yger 11 1 0 29 Nov 2021
Randomized Stochastic Gradient Descent Ascent Othmane Sebbouh Marco Cuturi Gabriel Peyré 110 7 0 25 Nov 2021
Input Convex Gradient Networks Jack Richter-Powell Jonathan Lorraine Brandon Amos 10 15 0 23 Nov 2021
Understanding Entropic Regularization in GANs Daria Reshetova Yikun Bai Xiugang Wu Ayfer Özgür 6 7 0 02 Nov 2021
Nearly Tight Convergence Bounds for Semi-discrete Entropic Optimal Transport Shin Kamada 13 15 0 25 Oct 2021
Statistical and Topological Properties of Gaussian Smoothed Sliced Probability Divergences A. Rakotomamonjy Mokhtar Z. Alaya Maxime Bérar Gilles Gasso 14 5 0 20 Oct 2021
Generative Modeling with Optimal Transport Maps Litu Rout Alexander Korotin Evgeny Burnaev OT DiffM 122 65 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 22 14 0 30 Sep 2021
Reversible Gromov-Monge Sampler for Simulation-Based Inference Y. Hur Wenxuan Guo Tengyuan Liang 31 9 0 28 Sep 2021
Entropic estimation of optimal transport maps Aram-Alexandre Pooladian Jonathan Niles-Weed OT 76 105 0 24 Sep 2021
Sinkhorn Distributionally Robust Optimization Jie Wang Rui Gao Yao Xie 29 35 0 24 Sep 2021
Optimal transport weights for causal inference Eric A. Dunipace CML OT 18 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 10 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 11 6 0 26 Jul 2021
AASAE: Augmentation-Augmented Stochastic Autoencoders William Falcon A. Jha Teddy Koker Kyunghyun Cho 11 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 17 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 15 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 11 20 0 12 Jul 2021
A stochastic Gauss-Newton algorithm for regularized semi-discrete optimal transport Bernard Bercu Jérémie Bigot S. Gadat Emilia Siviero 20 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 12 43 0 04 Jul 2021
Deep Inertial Navigation using Continuous Domain Adaptation and Optimal Transport Mohammed Alloulah Maximilian Arnold Anton Isopoussu OOD 16 2 0 29 Jun 2021
Asymptotics for semi-discrete entropic optimal transport Jason M. Altschuler Jonathan Niles-Weed Austin J. Stromme 11 27 0 22 Jun 2021
Discrepancy-based Inference for Intractable Generative Models using Quasi-Monte Carlo Ziang Niu J. Meier F. Briol 17 12 0 22 Jun 2021
Manifold Matching via Deep Metric Learning for Generative Modeling Mengyu Dai Haibin Hang GAN 11 9 0 20 Jun 2021
KALE Flow: A Relaxed KL Gradient Flow for Probabilities with Disjoint Support Pierre Glaser Michael Arbel A. Gretton 36 36 0 16 Jun 2021
Non-asymptotic convergence bounds for Wasserstein approximation using point clouds Q. Mérigot F. Santambrogio Clément Sarrazin 18 27 0 15 Jun 2021
Learning Revenue-Maximizing Auctions With Differentiable Matching Michael J. Curry Uro Lyi Tom Goldstein John P. Dickerson 11 20 0 15 Jun 2021
A Wasserstein Minimax Framework for Mixed Linear Regression Theo Diamandis Yonina C. Eldar Alireza Fallah Farzan Farnia Asuman Ozdaglar 17 6 0 14 Jun 2021
Separation Results between Fixed-Kernel and Feature-Learning Probability Metrics Carles Domingo-Enrich Youssef Mroueh 11 1 0 10 Jun 2021
Conditional COT-GAN for Video Prediction with Kernel Smoothing Tianlin Xu Beatrice Acciaio GAN AI4TS CML 11 4 0 10 Jun 2021
Partial Wasserstein and Maximum Mean Discrepancy distances for bridging the gap between outlier detection and drift detection T. Viehmann 11 4 0 09 Jun 2021
Neural Monge Map estimation and its applications JiaoJiao Fan Shu Liu Shaojun Ma Haomin Zhou Yongxin Chen OT 22 23 0 07 Jun 2021
k-Mixup Regularization for Deep Learning via Optimal Transport Kristjan Greenewald Anming Gu Mikhail Yurochkin Justin Solomon Edward Chien 28 17 0 05 Jun 2021
A Survey on Optimal Transport for Machine Learning: Theory and Applications Luis Caicedo Torres Luiz Manella Pereira M. Amini OOD OT 21 47 0 03 Jun 2021
MICo: Improved representations via sampling-based state similarity for Markov decision processes P. S. Castro Tyler Kastner Prakash Panangaden Mark Rowland 21 35 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
Diffusion Schrödinger Bridge with Applications to Score-Based Generative Modeling Valentin De Bortoli James Thornton J. Heng Arnaud Doucet DiffM OT 30 428 0 01 Jun 2021