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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
Zero-Shot Recognition via Optimal Transport Wenlin Wang Hongteng Xu Guoyin Wang Wenqi Wang Lawrence Carin OT 33 2 0 20 Oct 2019
Differentiable Deep Clustering with Cluster Size Constraints Aude Genevay Gabriel Dulac-Arnold Jean-Philippe Vert 53 40 0 20 Oct 2019
Quantitative stability of optimal transport maps and linearization of the 2-Wasserstein space Q. Mérigot Alex Delalande Frédéric Chazal OT 55 44 0 14 Oct 2019
Prescribed Generative Adversarial Networks Adji Bousso Dieng Francisco J. R. Ruiz David M. Blei Michalis K. Titsias GAN DRL 80 62 0 09 Oct 2019
Learning with minibatch Wasserstein : asymptotic and gradient properties Kilian Fatras Younes Zine Rémi Flamary Rémi Gribonval Nicolas Courty OT 102 96 0 09 Oct 2019
How Well Do WGANs Estimate the Wasserstein Metric? Anton Mallasto Guido Montúfar Augusto Gerolin 53 26 0 09 Oct 2019
Spatio-Temporal Alignments: Optimal transport through space and time H. Janati Marco Cuturi Alexandre Gramfort OT AI4TS 64 29 0 09 Oct 2019
A mathematical theory of cooperative communication Pei Wang Junqi Wang P. Paranamana Patrick Shafto 79 49 0 07 Oct 2019
On the estimation of the Wasserstein distance in generative models Thomas Pinetz Daniel Soukup Thomas Pock GAN 75 9 0 02 Oct 2019
Learning transport cost from subset correspondence Ruishan Liu Akshay Balsubramani James Zou OT 54 14 0 29 Sep 2019
UNITER: UNiversal Image-TExt Representation Learning Yen-Chun Chen Linjie Li Licheng Yu Ahmed El Kholy Faisal Ahmed Zhe Gan Yu Cheng Jingjing Liu VLM OT 134 449 0 25 Sep 2019
Enhancing Traffic Scene Predictions with Generative Adversarial Networks Peter König Sandra Aigner Marco Körner 32 3 0 24 Sep 2019
Estimation of Wasserstein distances in the Spiked Transport Model Jonathan Niles-Weed Philippe Rigollet 87 103 0 16 Sep 2019
Wasserstein Distributionally Robust Optimization: Theory and Applications in Machine Learning Daniel Kuhn Peyman Mohajerin Esfahani Viet Anh Nguyen Soroosh Shafieezadeh-Abadeh OOD 68 397 0 23 Aug 2019
Fast convergence of empirical barycenters in Alexandrov spaces and the Wasserstein space Thibaut Le Gouic Q. Paris Philippe Rigollet Austin J. Stromme 111 52 0 02 Aug 2019
Defense Against Adversarial Attacks Using Feature Scattering-based Adversarial Training Haichao Zhang Jianyu Wang AAML 112 231 0 24 Jul 2019
Optimal Transport-based Alignment of Learned Character Representations for String Similarity Derek Tam Nicholas Monath Ari Kobren Aaron Traylor Rajarshi Das Andrew McCallum 61 15 0 23 Jul 2019
Statistical data analysis in the Wasserstein space Jérémie Bigot 69 32 0 19 Jul 2019
k-GANs: Ensemble of Generative Models with Semi-Discrete Optimal Transport L. Ambrogioni Umut Güçlü Marcel van Gerven GAN 28 4 0 09 Jul 2019
Adversarial Computation of Optimal Transport Maps Jacob Leygonie Jennifer She Amjad Almahairi Sai Rajeswar Aaron Courville GAN OT 75 21 0 24 Jun 2019
GAIT: A Geometric Approach to Information Theory Jose Gallego-Posada Ankit Vani Max Schwarzer Simon Lacoste-Julien 69 8 0 19 Jun 2019
Minimum Stein Discrepancy Estimators Alessandro Barp François‐Xavier Briol Andrew B. Duncan Mark Girolami Lester W. Mackey 82 93 0 19 Jun 2019
Local Bures-Wasserstein Transport: A Practical and Fast Mapping Approximation Andrés Hoyos-Idrobo OT 28 0 0 19 Jun 2019
Statistical Inference for Generative Models with Maximum Mean Discrepancy François‐Xavier Briol Alessandro Barp Andrew B. Duncan Mark Girolami 60 72 0 13 Jun 2019
Asymptotic Guarantees for Learning Generative Models with the Sliced-Wasserstein Distance Kimia Nadjahi Alain Durmus Umut Simsekli Roland Badeau MedIm 76 63 0 11 Jun 2019
Maximum Mean Discrepancy Gradient Flow Michael Arbel Anna Korba Adil Salim Arthur Gretton 132 164 0 11 Jun 2019
A gradual, semi-discrete approach to generative network training via explicit Wasserstein minimization Yucheng Chen Matus Telgarsky Chao Zhang Bolton Bailey Daniel J. Hsu Jian-wei Peng GAN OT 69 17 0 08 Jun 2019
GOT: An Optimal Transport framework for Graph comparison Hermina Petric Maretic Mireille El Gheche Giovanni Chierchia P. Frossard OT 151 120 0 05 Jun 2019
Sinkhorn Barycenters with Free Support via Frank-Wolfe Algorithm Giulia Luise Saverio Salzo Massimiliano Pontil C. Ciliberto 85 69 0 30 May 2019
Statistical bounds for entropic optimal transport: sample complexity and the central limit theorem Gonzalo E. Mena Jonathan Niles-Weed OT 88 167 0 28 May 2019
Utility/Privacy Trade-off through the lens of Optimal Transport Etienne Boursier Vianney Perchet 59 8 0 27 May 2019
Subspace Detours: Building Transport Plans that are Optimal on Subspace Projections Boris Muzellec Marco Cuturi OT 85 31 0 24 May 2019
Geometric Losses for Distributional Learning A. Mensch Mathieu Blondel Gabriel Peyré 143 16 0 15 May 2019
Minimax estimation of smooth optimal transport maps Jan-Christian Hütter Philippe Rigollet OT 82 28 0 14 May 2019
Learning Generative Models across Incomparable Spaces Charlotte Bunne David Alvarez-Melis Andreas Krause Stefanie Jegelka GAN 84 112 0 14 May 2019
Learning Embeddings into Entropic Wasserstein Spaces Charlie Frogner F. Mirzazadeh Justin Solomon 74 32 0 08 May 2019
Sliced Wasserstein Generative Models Jiqing Wu Zhiwu Huang Dinesh Acharya Wen Li Janine Thoma D. Paudel Luc Van Gool DiffM 133 126 0 10 Apr 2019
Wasserstein Adversarial Regularization (WAR) on label noise Kilian Fatras B. Bushan Sylvain Lobry Rémi Flamary D. Tuia Nicolas Courty 81 25 0 08 Apr 2019
The Born Supremacy: Quantum Advantage and Training of an Ising Born Machine Brian Coyle Daniel Mills V. Danos E. Kashefi 106 158 0 03 Apr 2019
Feature Intertwiner for Object Detection Hongyang Li Bo Dai Shaoshuai Shi Wanli Ouyang Xiaogang Wang OOD 47 13 0 28 Mar 2019
Are Few-Shot Learning Benchmarks too Simple ? Solving them without Task Supervision at Test-Time Gabriel Huang Hugo Larochelle Simon Lacoste-Julien SSL OOD 130 21 0 22 Feb 2019
Sinkhorn Divergence of Topological Signature Estimates for Time Series Classification C. Stephen 22 0 0 14 Feb 2019
Wasserstein Barycenter Model Ensembling Pierre Dognin Igor Melnyk Youssef Mroueh Jerret Ross Cicero Nogueira dos Santos Tom Sercu 79 25 0 13 Feb 2019
(q,p)-Wasserstein GANs: Comparing Ground Metrics for Wasserstein GANs Anton Mallasto J. Frellsen Wouter Boomsma Aasa Feragen 60 15 0 10 Feb 2019
Minimax estimation of smooth densities in Wasserstein distance Jonathan Niles-Weed Quentin Berthet OT 79 38 0 05 Feb 2019
AutoShuffleNet: Learning Permutation Matrices via an Exact Lipschitz Continuous Penalty in Deep Convolutional Neural Networks J. Lyu Shuai Zhang Y. Qi Jack Xin 73 27 0 24 Jan 2019
Improving Sequence-to-Sequence Learning via Optimal Transport Liqun Chen Yizhe Zhang Ruiyi Zhang Chenyang Tao Zhe Gan Haichao Zhang Bai Li Dinghan Shen Changyou Chen Lawrence Carin OT 76 94 0 18 Jan 2019
Asymptotic distribution and convergence rates of stochastic algorithms for entropic optimal transportation between probability measures Bernard Bercu Jérémie Bigot 66 19 0 21 Dec 2018
Massively scalable Sinkhorn distances via the Nyström method Jason M. Altschuler Francis R. Bach Alessandro Rudi Jonathan Niles-Weed 70 111 0 12 Dec 2018
Stochastic Deep Networks Gwendoline de Bie Gabriel Peyré Marco Cuturi 107 21 0 19 Nov 2018