Learning Generative Models with Sinkhorn Divergences

1 June 2017

Papers citing "Learning Generative Models with Sinkhorn Divergences"

50 / 375 papers shown

Title
Markovian Sliced Wasserstein Distances: Beyond Independent Projections Khai Nguyen Tongzheng Ren Nhat Ho 16 7 0 10 Jan 2023
Optimal transport map estimation in general function spaces Vincent Divol Jonathan Niles-Weed Aram-Alexandre Pooladian OT 22 22 0 07 Dec 2022
Estimating Regression Predictive Distributions with Sample Networks Ali Harakeh Jordan S. K. Hu Naiqing Guan Steven L. Waslander Liam Paull BDL UQCV 22 4 0 24 Nov 2022
Mirror Sinkhorn: Fast Online Optimization on Transport Polytopes Marin Ballu Quentin Berthet 25 7 0 18 Nov 2022
Unbalanced Optimal Transport, from Theory to Numerics Thibault Séjourné Gabriel Peyré Franccois-Xavier Vialard OT 25 47 0 16 Nov 2022
Lipschitz-regularized gradient flows and generative particle algorithms for high-dimensional scarce data Hyemin Gu P. Birmpa Yannis Pantazis Luc Rey-Bellet M. Katsoulakis 16 2 0 31 Oct 2022
Minimum Kernel Discrepancy Estimators Chris J. Oates 22 10 0 28 Oct 2022
Budget-Constrained Bounds for Mini-Batch Estimation of Optimal Transport David Alvarez-Melis Nicolò Fusi Lester W. Mackey Tal Wagner OT 14 1 0 24 Oct 2022
Partial Identification of Treatment Effects with Implicit Generative Models Vahid Balazadeh Meresht Vasilis Syrgkanis Rahul G. Krishnan CML 18 19 0 14 Oct 2022
On the potential benefits of entropic regularization for smoothing Wasserstein estimators Jérémie Bigot Paul Freulon B. Hejblum Arthur Leclaire OT 27 2 0 13 Oct 2022
Gaussian Processes on Distributions based on Regularized Optimal Transport F. Bachoc Louis Bethune Alberto González Sanz Jean-Michel Loubes GP OT 12 7 0 12 Oct 2022
VoLTA: Vision-Language Transformer with Weakly-Supervised Local-Feature Alignment Shraman Pramanick Li Jing Sayan Nag Jiachen Zhu Hardik Shah Yann LeCun Ramalingam Chellappa 24 21 0 09 Oct 2022
Improving Generative Flow Networks with Path Regularization A. Do Duy-Tung Dinh T. Nguyen Khuong N. Nguyen Stanley Osher Nhat Ho AI4CE 21 4 0 29 Sep 2022
Hierarchical Sliced Wasserstein Distance Khai Nguyen Tongzheng Ren Huy Nguyen Litu Rout T. Nguyen Nhat Ho 26 19 0 27 Sep 2022
Wasserstein $K$ -means for clustering probability distributions Yubo Zhuang Xiaohui Chen Yun Yang 13 23 0 14 Sep 2022
Learning Deep Optimal Embeddings with Sinkhorn Divergences S. Roy Yan Han Mehrtash Harandi L. Petersson 12 0 0 14 Sep 2022
Meta-Learning with Less Forgetting on Large-Scale Non-Stationary Task Distributions Zhenyi Wang Li Shen Le Fang Qiuling Suo Dongling Zhan Tiehang Duan Mingchen Gao OOD CLL 13 14 0 03 Sep 2022
Discovering Conservation Laws using Optimal Transport and Manifold Learning Peter Y. Lu Rumen Dangovski M. Soljavcić 27 17 0 31 Aug 2022
Multiview Regenerative Morphing with Dual Flows Chih-Jung Tsai Cheng Sun Hwann-Tzong Chen 3DH 21 1 0 02 Aug 2022
The derivatives of Sinkhorn-Knopp converge Edouard Pauwels Samuel Vaiter 25 5 0 26 Jul 2022
Weak limits of entropy regularized Optimal Transport; potentials, plans and divergences Alberto González Sanz Jean-Michel Loubes Jonathan Niles-Weed OT 14 22 0 15 Jul 2022
Transferability-Guided Cross-Domain Cross-Task Transfer Learning Yang Tan Enming Zhang Yang Li Shao-Lun Huang Xiaoping Zhang OT 33 9 0 12 Jul 2022
Multisymplectic Formulation of Deep Learning Using Mean--Field Type Control and Nonlinear Stability of Training Algorithm Nader Ganaba 6 0 0 07 Jul 2022
Diffeomorphic Registration using Sinkhorn Divergences Lucas de Lara Alberto González Sanz Jean-Michel Loubes FedML 11 8 0 28 Jun 2022
On Certifying and Improving Generalization to Unseen Domains Akshay Mehra B. Kailkhura Pin-Yu Chen Jihun Hamm OOD 18 4 0 24 Jun 2022
Approximating 1-Wasserstein Distance with Trees M. Yamada Yuki Takezawa Ryoma Sato Hang Bao Zornitsa Kozareva Sujith Ravi 47 8 0 24 Jun 2022
On making optimal transport robust to all outliers Kilian Fatras OT 13 0 0 23 Jun 2022
Optimal transport meets noisy label robust loss and MixUp regularization for domain adaptation Kilian Fatras Hiroki Naganuma Ioannis Mitliagkas OOD 14 6 0 22 Jun 2022
Rethinking Initialization of the Sinkhorn Algorithm James Thornton Marco Cuturi OT 21 10 0 15 Jun 2022
Loss Functions for Classification using Structured Entropy B. Lucena 14 3 0 14 Jun 2022
Asymptotics of smoothed Wasserstein distances in the small noise regime Yunzi Ding Jonathan Niles-Weed OT 16 2 0 13 Jun 2022
Meta Optimal Transport Brandon Amos Samuel N. Cohen Giulia Luise I. Redko OT 22 22 0 10 Jun 2022
Causality Learning With Wasserstein Generative Adversarial Networks H. Petkov Colin Hanley Feng Dong CML GAN OOD 12 0 0 03 Jun 2022
Distributional Convergence of the Sliced Wasserstein Process Jiaqi Xi Jonathan Niles-Weed 19 6 0 01 Jun 2022
Hilbert Curve Projection Distance for Distribution Comparison Tao Li Cheng Meng Hongteng Xu Jun Yu 39 13 0 30 May 2022
Low-rank Optimal Transport: Approximation, Statistics and Debiasing M. Scetbon Marco Cuturi OT 24 16 0 24 May 2022
Time-series Transformer Generative Adversarial Networks Padmanaba Srinivasan William J. Knottenbelt AI4TS 21 13 0 23 May 2022
A Unified Framework for Implicit Sinkhorn Differentiation Marvin Eisenberger Aysim Toker Laura Leal-Taixé Florian Bernard Daniel Cremers AI4CE 48 23 0 13 May 2022
Domain Adaptation meets Individual Fairness. And they get along Debarghya Mukherjee Felix Petersen Mikhail Yurochkin Yuekai Sun FaML 19 16 0 01 May 2022
An improved central limit theorem and fast convergence rates for entropic transportation costs E. del Barrio Alberto González Sanz Jean-Michel Loubes Jonathan Niles-Weed OT 34 32 0 19 Apr 2022
Hierarchical Optimal Transport for Comparing Histopathology Datasets A. Yeaton Rahul G. Krishnan Rebecca J. Mieloszyk David Alvarez-Melis G. Huynh OT 17 9 0 18 Apr 2022
Neural Estimation of the Rate-Distortion Function With Applications to Operational Source Coding E. Lei Hamed Hassani Shirin Saeedi Bidokhti 11 19 0 04 Apr 2022
DAG-WGAN: Causal Structure Learning With Wasserstein Generative Adversarial Networks H. Petkov Colin Hanley Feng Dong GAN OOD CML 27 6 0 01 Apr 2022
OTFace: Hard Samples Guided Optimal Transport Loss for Deep Face Representation J. Qian Shumin Zhu Chao-Yue Zhao Jian Yang Wai Keung Wong CVBM 24 5 0 28 Mar 2022
Wasserstein Distributionally Robust Optimization with Wasserstein Barycenters Tim Tsz-Kit Lau Han Liu OOD 32 2 0 23 Mar 2022
SiMCa: Sinkhorn Matrix Factorization with Capacity Constraints Eric Daoud Luca Ganassali Antoine Baker Marc Lelarge 23 0 0 18 Mar 2022
Adversarial Support Alignment Shangyuan Tong T. Garipov Yang Zhang Shiyu Chang Tommi Jaakkola 8 9 0 16 Mar 2022
Interpretable Dysarthric Speaker Adaptation based on Optimal-Transport Rosanna Turrisi Leonardo Badino 11 3 0 14 Mar 2022
Partial Wasserstein Adversarial Network for Non-rigid Point Set Registration Zifeng Wang Nan Xue Ling Lei Guisong Xia 3DPC 18 3 0 04 Mar 2022
Debiaser Beware: Pitfalls of Centering Regularized Transport Maps Aram-Alexandre Pooladian Marco Cuturi Jonathan Niles-Weed OT 27 16 0 17 Feb 2022