Learning Generative Models with Sinkhorn Divergences

1 June 2017

Papers citing "Learning Generative Models with Sinkhorn Divergences"

50 / 375 papers shown

Title
Flow Matching Ergodic Coverage Max Muchen Sun Allison Pinosky Todd Murphey 28 0 0 24 Apr 2025
Resonances in reflective Hamiltonian Monte Carlo Namu Kroupa Gábor Csányi Will Handley 31 0 0 16 Apr 2025
Towards generalizable single-cell perturbation modeling via the Conditional Monge Gap Alice Driessen Benedek Harsanyi Marianna Rapsomaniki Jannis Born AI4CE 34 0 0 11 Apr 2025
A Truncated Newton Method for Optimal Transport Mete Kemertas Amir-massoud Farahmand Allan D. Jepson OT 46 0 0 02 Apr 2025
Nested Stochastic Gradient Descent for (Generalized) Sinkhorn Distance-Regularized Distributionally Robust Optimization Y. Yang Yi Zhou Zhaosong Lu 49 0 0 29 Mar 2025
Properties of Wasserstein Gradient Flows for the Sliced-Wasserstein Distance Christophe Vauthier Quentin Mérigot Anna Korba 37 0 0 10 Feb 2025
Fused Gromov-Wasserstein Variance Decomposition with Linear Optimal Transport Michael Wilson Tom Needham A. Srivastava OT 29 0 0 15 Nov 2024
Implicit Dynamical Flow Fusion (IDFF) for Generative Modeling Mohammad R. Rezaei Rahul G. Krishnan Milos R. Popovic M. Lankarany DiffM 24 0 0 22 Sep 2024
A Sinkhorn Regularized Adversarial Network for Image Guided DEM Super-resolution using Frequency Selective Hybrid Graph Transformer Subhajit Paul Ashutosh Gupta 18 0 0 21 Sep 2024
Multimodal Prototyping for cancer survival prediction Andrew H. Song Richard J. Chen Guillaume Jaume Anurag J. Vaidya Alexander S. Baras Faisal Mahmood 24 12 0 28 Jun 2024
Estimating Long-term Heterogeneous Dose-response Curve: Generalization Bound Leveraging Optimal Transport Weights Zeqin Yang Weilin Chen Ruichu Cai Yuguang Yan Zhifeng Hao Zhipeng Yu Zhichao Zou Zhen Peng Jiecheng Guo 54 3 0 27 Jun 2024
Repeat and Concatenate: 2D to 3D Image Translation with 3D to 3D Generative Modeling Abril Corona-Figueroa Hubert P. H. Shum Chris G. Willcocks 24 0 0 26 Jun 2024
Differentiable Cost-Parameterized Monge Map Estimators Samuel Howard George Deligiannidis Patrick Rebeschini James Thornton OT 36 1 0 12 Jun 2024
Progressive Entropic Optimal Transport Solvers Parnian Kassraie Aram-Alexandre Pooladian Michal Klein James Thornton Jonathan Niles-Weed Marco Cuturi OT 30 4 0 07 Jun 2024
SAVA: Scalable Learning-Agnostic Data Valuation Samuel Kessler Tam Le Vu Nguyen TDI 51 0 0 03 Jun 2024
On the Convergence of the Sinkhorn-Knopp Algorithm with Sparse Cost Matrices Jose Rafael Espinosa Mena 16 0 0 30 May 2024
FASTopic: A Fast, Adaptive, Stable, and Transferable Topic Modeling Paradigm Xiaobao Wu Thong Nguyen Delvin Ce Zhang William Yang Wang A. Luu 37 4 0 28 May 2024
Diffusion Bridge AutoEncoders for Unsupervised Representation Learning Yeongmin Kim Kwanghyeon Lee Minsang Park Byeonghu Na Il-Chul Moon DiffM 42 2 0 27 May 2024
Statistical and Computational Guarantees of Kernel Max-Sliced Wasserstein Distances Jie Wang M. Boedihardjo Yao Xie 46 1 0 24 May 2024
Fisher Flow Matching for Generative Modeling over Discrete Data Oscar Davis Samuel Kessler Mircea Petrache .Ismail .Ilkan Ceylan Michael M. Bronstein A. Bose 40 16 0 23 May 2024
Semi-Discrete Optimal Transport: Nearly Minimax Estimation With Stochastic Gradient Descent and Adaptive Entropic Regularization Ferdinand Genans Antoine Godichon-Baggioni Franccois-Xavier Vialard Olivier Wintenberger 24 0 0 23 May 2024
Stochastic Learning of Computational Resource Usage as Graph Structured Multimarginal Schrödinger Bridge Georgiy A. Bondar Robert Gifford L. T. Phan Abhishek Halder 28 0 0 21 May 2024
Revisiting Deep Audio-Text Retrieval Through the Lens of Transportation Manh Luong Khai Nguyen Nhat Ho Reza Haf D.Q. Phung Lizhen Qu 30 12 0 16 May 2024
Deep MMD Gradient Flow without adversarial training Alexandre Galashov Valentin De Bortoli Arthur Gretton DiffM 32 7 0 10 May 2024
A New Robust Partial $p$ -Wasserstein-Based Metric for Comparing Distributions S. Raghvendra Pouyan Shirzadian Kaiyi Zhang 34 1 0 06 May 2024
Get more for less: Principled Data Selection for Warming Up Fine-Tuning in LLMs Feiyang Kang H. Just Yifan Sun Himanshu Jahagirdar Yuanzhi Zhang Rongxing Du Anit Kumar Sahu Ruoxi Jia 54 17 0 05 May 2024
Wasserstein Wormhole: Scalable Optimal Transport Distance with Transformers D. Haviv Russell Z. Kunes Thomas Dougherty Cassandra Burdziak T. Nawy Anna Gilbert D. Pe’er OT 22 5 0 15 Apr 2024
Gaussian-Smoothed Sliced Probability Divergences Mokhtar Z. Alaya A. Rakotomamonjy Maxime Bérar Gilles Gasso 31 0 0 04 Apr 2024
Propensity Score Alignment of Unpaired Multimodal Data Johnny Xi Jason S. Hartford 24 2 0 02 Apr 2024
Conditional Wasserstein Distances with Applications in Bayesian OT Flow Matching Jannis Chemseddine Paul Hagemann Gabriele Steidl Christian Wald 38 9 0 27 Mar 2024
On the nonconvexity of some push-forward constraints and its consequences in machine learning Lucas de Lara Mathis Deronzier Alberto González Sanz Virgile Foy 13 0 0 12 Mar 2024
A Sinkhorn-type Algorithm for Constrained Optimal Transport Xun Tang Holakou Rahmanian Michael Shavlovsky K. K. Thekumparampil Tesi Xiao Lexing Ying 26 1 0 08 Mar 2024
On a Neural Implementation of Brenier's Polar Factorization Nina Vesseron Marco Cuturi 39 2 0 05 Mar 2024
Sinkhorn Distance Minimization for Knowledge Distillation Xiao Cui Yulei Qin Yuting Gao Enwei Zhang Zihan Xu Tong Wu Ke Li Xing Sun Wen-gang Zhou Houqiang Li 62 5 0 27 Feb 2024
DySLIM: Dynamics Stable Learning by Invariant Measure for Chaotic Systems Yair Schiff Zhong Yi Wan Jeffrey B. Parker Stephan Hoyer Volodymyr Kuleshov Fei Sha Leonardo Zepeda-Núnez 28 11 0 06 Feb 2024
On the Affinity, Rationality, and Diversity of Hierarchical Topic Modeling Xiaobao Wu Fengjun Pan Thong Nguyen Yichao Feng Chaoqun Liu Cong-Duy Nguyen A. Luu 21 21 0 25 Jan 2024
Neural Sinkhorn Gradient Flow Huminhao Zhu Fangyikang Wang Chao Zhang Han Zhao Hui Qian 27 5 0 25 Jan 2024
Spectral Clustering for Discrete Distributions Zixiao Wang Dong Qiao Jicong Fan 12 0 0 25 Jan 2024
Accelerating Sinkhorn Algorithm with Sparse Newton Iterations Xun Tang Michael Shavlovsky Holakou Rahmanian Elisa Tardini K. K. Thekumparampil Tesi Xiao Lexing Ying OT 31 4 0 20 Jan 2024
Learning from small data sets: Patch-based regularizers in inverse problems for image reconstruction Moritz Piening Fabian Altekrüger J. Hertrich Paul Hagemann Andrea Walther Gabriele Steidl 24 6 0 27 Dec 2023
PULASki: Learning inter-rater variability using statistical distances to improve probabilistic segmentation S. Chatterjee Franziska Gaidzik Alessandro Sciarra Hendrik Mattern G. Janiga Oliver Speck Andreas Nürnberger S. Pathiraja 44 0 0 25 Dec 2023
Differentially Private Gradient Flow based on the Sliced Wasserstein Distance Ilana Sebag Muni Sreenivas Pydi Jean-Yves Franceschi Alain Rakotomamonjy Mike Gartrell Jamal Atif Alexandre Allauzen 24 2 0 13 Dec 2023
DeepEMD: A Transformer-based Fast Estimation of the Earth Mover's Distance A. Sinha F. Fleuret 22 3 0 16 Nov 2023
Unsupervised approaches based on optimal transport and convex analysis for inverse problems in imaging M. Carioni Subhadip Mukherjee Hongwei Tan Junqi Tang MedIm 29 3 0 15 Nov 2023
Structured Transforms Across Spaces with Cost-Regularized Optimal Transport Othmane Sebbouh Marco Cuturi Gabriel Peyré OT 17 4 0 09 Nov 2023
Time-series Generation by Contrastive Imitation Daniel Jarrett Ioana Bica M. Schaar AI4TS 13 24 0 02 Nov 2023
Estimating the Rate-Distortion Function by Wasserstein Gradient Descent Yibo Yang Stephan Eckstein Marcel Nutz Stephan Mandt 8 9 0 29 Oct 2023
Causal Modeling with Stationary Diffusions Lars Lorch Andreas Krause Bernhard Schölkopf DiffM 12 7 0 26 Oct 2023
A Specialized Semismooth Newton Method for Kernel-Based Optimal Transport Tianyi Lin Marco Cuturi Michael I. Jordan OT 36 0 0 21 Oct 2023
Optimal Transport for Measures with Noisy Tree Metric Tam Le Truyen V. Nguyen Kenji Fukumizu OT 30 4 0 20 Oct 2023