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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
Unsupervised approaches based on optimal transport and convex analysis for inverse problems in imaging M. Carioni Subhadip Mukherjee Hongwei Tan Junqi Tang MedIm 82 4 0 15 Nov 2023
Structured Transforms Across Spaces with Cost-Regularized Optimal Transport Othmane Sebbouh Marco Cuturi Gabriel Peyré OT 74 4 0 09 Nov 2023
Time-series Generation by Contrastive Imitation Daniel Jarrett Ioana Bica M. Schaar AI4TS 86 24 0 02 Nov 2023
Estimating the Rate-Distortion Function by Wasserstein Gradient Descent Yibo Yang Stephan Eckstein Marcel Nutz Stephan Mandt 79 10 0 29 Oct 2023
Causal Modeling with Stationary Diffusions Lars Lorch Andreas Krause Bernhard Schölkopf DiffM 141 13 0 26 Oct 2023
A Specialized Semismooth Newton Method for Kernel-Based Optimal Transport Tianyi Lin Marco Cuturi Michael I. Jordan OT 82 0 0 21 Oct 2023
Optimal Transport for Measures with Noisy Tree Metric Tam Le Truyen V. Nguyen Kenji Fukumizu OT 98 6 0 20 Oct 2023
Y-Diagonal Couplings: Approximating Posteriors with Conditional Wasserstein Distances Jannis Chemseddine Paul Hagemann Christian Wald 112 3 0 20 Oct 2023
Robust Graph Matching Using An Unbalanced Hierarchical Optimal Transport Framework Haoran Cheng Dixin Luo Hongteng Xu OT 73 0 0 18 Oct 2023
On Unsupervised Image-to-image translation and GAN stability BahaaEddin AlAila Zahra Jandaghi Abolfazl Farahani M. Al-Saad GAN 50 1 0 18 Oct 2023
Stabilizing Subject Transfer in EEG Classification with Divergence Estimation Niklas Smedemark-Margulies Ye Wang T. Koike-Akino Jing Liu K. Parsons Yunus Bicer Deniz Erdogmus 62 0 0 12 Oct 2023
Sparsistency for Inverse Optimal Transport Francisco Andrade Gabriel Peyré Clarice Poon 61 6 0 09 Oct 2023
SE(3)-Stochastic Flow Matching for Protein Backbone Generation A. Bose Tara Akhound-Sadegh Guillaume Huguet Kilian Fatras Jarrid Rector-Brooks Cheng-Hao Liu A. Nica Maksym Korablyov Michael M. Bronstein Alexander Tong DiffM 121 85 0 03 Oct 2023
Stochastic force inference via density estimation Victor Chardès Suryanarayana Maddu Michael J. Shelley DiffM 51 4 0 03 Oct 2023
A Unified View of Differentially Private Deep Generative Modeling Dingfan Chen Raouf Kerkouche Mario Fritz SyDa 90 5 0 27 Sep 2023
Generating and Imputing Tabular Data via Diffusion and Flow-based Gradient-Boosted Trees Alexia Jolicoeur-Martineau Kilian Fatras Tal Kachman 110 41 0 18 Sep 2023
Topological Node2vec: Enhanced Graph Embedding via Persistent Homology Yasuaki Hiraoka Yusuke Imoto Killian Meehan Théo Lacombe Toshiaki Yachimura 61 5 0 15 Sep 2023
Match-And-Deform: Time Series Domain Adaptation through Optimal Transport and Temporal Alignment Franccois Painblanc Laetitia Chapel Nicolas Courty Chloé Friguet Charlotte Pelletier R. Tavenard AI4TS OOD 60 7 0 24 Aug 2023
Statistically Optimal Generative Modeling with Maximum Deviation from the Empirical Distribution Elen Vardanyan Sona Hunanyan T. Galstyan A. Minasyan A. Dalalyan 121 2 0 31 Jul 2023
Neural Schrödinger Bridge with Sinkhorn Losses: Application to Data-driven Minimum Effort Control of Colloidal Self-assembly Iman Nodozi Charlie Yan Mira M. Khare A. Halder A. Mesbah 86 5 0 26 Jul 2023
Properties of Discrete Sliced Wasserstein Losses Eloi Tanguy Rémi Flamary J. Delon 71 10 0 19 Jul 2023
Differentiable Transportation Pruning Yun-qiang Li Jan van Gemert Torsten Hoefler Bert Moons E. Eleftheriou Bram-Ernst Verhoef OT 89 8 0 17 Jul 2023
Efficient and Accurate Optimal Transport with Mirror Descent and Conjugate Gradients Mete Kemertas Allan D. Jepson Amir-massoud Farahmand OT 139 3 0 17 Jul 2023
Simulation-free Schrödinger bridges via score and flow matching Alexander Tong Nikolay Malkin Kilian Fatras Lazar Atanackovic Yanlei Zhang G. Huguet Guy Wolf Yoshua Bengio DiffM OT 122 40 0 07 Jul 2023
Performance Scaling via Optimal Transport: Enabling Data Selection from Partially Revealed Sources Feiyang Kang H. Just Anit Kumar Sahu R. Jia 97 11 0 05 Jul 2023
Unbalanced Optimal Transport: A Unified Framework for Object Detection Henri De Plaen Pierre-François De Plaen Johan A. K. Suykens Marc Proesmans Tinne Tuytelaars Luc Van Gool OT 67 10 0 05 Jul 2023
SoK: Privacy-Preserving Data Synthesis Yuzheng Hu Fan Wu Yue Liu Yunhui Long Gonzalo Munilla Garrido Chang Ge Bolin Ding David A. Forsyth Yue Liu Basel Alomair 116 33 0 05 Jul 2023
On a Relation Between the Rate-Distortion Function and Optimal Transport Eric Lei Hamed Hassani Shirin Saeedi Bidokhti OT 62 2 0 01 Jul 2023
Recent Advances in Optimal Transport for Machine Learning Eduardo Fernandes Montesuma Fred-Maurice Ngole-Mboula Antoine Souloumiac OOD OT 105 39 0 28 Jun 2023
Provably Convergent Policy Optimization via Metric-aware Trust Region Methods Jun Song Niao He Lijun Ding Chaoyue Zhao 85 2 0 25 Jun 2023
Training generative models from privatized data Daria Reshetova Wei-Ning Chen Ayfer Özgür FedML 62 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
Effective Neural Topic Modeling with Embedding Clustering Regularization Xiaobao Wu Xinshuai Dong Thong Nguyen Anh Tuan Luu BDL 138 44 0 07 Jun 2023
Coupled Variational Autoencoder Xiaoran Hao Patrick Shafto BDL DRL 74 4 0 05 Jun 2023
Bringing regularized optimal transport to lightspeed: a splitting method adapted for GPUs Jacob Lindbäck Zesen Wang Mikael Johansson OT 102 1 0 29 May 2023
Feature-aligned N-BEATS with Sinkhorn divergence Joon-Young Lee Myeongho Jeon Myung-joo Kang Kyung-soon Park AI4TS 61 0 0 24 May 2023
Weak Limits for Empirical Entropic Optimal Transport: Beyond Smooth Costs Alberto González Sanz Shayan Hundrieser OT 48 11 0 16 May 2023
Speeding up Monte Carlo Integration: Control Neighbors for Optimal Convergence Rémi Leluc Franccois Portier Johan Segers Aigerim Zhuman 81 8 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 115 62 0 28 Apr 2023
Multisample Flow Matching: Straightening Flows with Minibatch Couplings Aram-Alexandre Pooladian Heli Ben-Hamu Carles Domingo-Enrich Brandon Amos Y. Lipman Ricky T. Q. Chen 126 150 0 28 Apr 2023
Nearest-Neighbor Sampling Based Conditional Independence Testing Shuai Li Ziqi Chen Hong-Tu Zhu Christina Dan Wang Wang Wen 36 4 0 09 Apr 2023
Keypoint-Guided Optimal Transport Xiang Gu Yucheng Yang Weizhen Zeng Jian Sun Zongben Xu 84 1 0 23 Mar 2023
Sinkhorn-Flow: Predicting Probability Mass Flow in Dynamical Systems Using Optimal Transport Mukul Bhutani J. Zico Kolter OT AI4TS 70 0 0 14 Mar 2023
Light Unbalanced Optimal Transport Milena Gazdieva Arip Asadulaev Alexander Korotin Evgeny Burnaev OT 73 2 0 14 Mar 2023
An Approximation Theory Framework for Measure-Transport Sampling Algorithms Ricardo Baptista Bamdad Hosseini Nikola B. Kovachki Youssef M. Marzouk A. Sagiv OT 98 17 0 27 Feb 2023
On Deep Generative Models for Approximation and Estimation of Distributions on Manifolds Biraj Dahal Alex Havrilla Minshuo Chen Tuo Zhao Wenjing Liao GAN 61 10 0 25 Feb 2023
Transformed Distribution Matching for Missing Value Imputation He Zhao Ke Sun Amir Dezfouli Edwin V. Bonilla 94 21 0 20 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
Tetris-inspired detector with neural network for radiation mapping Ryotaro Okabe Shangjie Xue Jiankai Yu Tongtong Liu Benoit Forget Stefanie Jegelka G. Kohse Lin-Wen Hu Mingda Li 23 5 0 07 Feb 2023