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Learning Generative Models with Sinkhorn Divergences

International Conference on Artificial Intelligence and Statistics (AISTATS), 2017

1 June 2017

Papers citing "Learning Generative Models with Sinkhorn Divergences"

50 / 397 papers shown

Title
Super-efficiency of automatic differentiation for functions defined as a minimumInternational Conference on Machine Learning (ICML), 2020 Pierre Ablin Gabriel Peyré Thomas Moreau 186 42 0 10 Feb 2020
Statistical Optimal Transport posed as Learning Kernel EmbeddingNeural Information Processing Systems (NeurIPS), 2020 SakethaNath Jagarlapudi Pratik Jawanpuria OT 156 17 0 08 Feb 2020
Geometric Dataset Distances via Optimal TransportNeural Information Processing Systems (NeurIPS), 2020 David Alvarez-Melis Nicolò Fusi OT 219 230 0 07 Feb 2020
Learning Implicit Generative Models with Theoretical Guarantees Yuan Gao Jian Huang Yuling Jiao Jin Liu 154 7 0 07 Feb 2020
Fast and Robust Comparison of Probability Measures in Heterogeneous Spaces Ryoma Sato Marco Cuturi M. Yamada H. Kashima 161 26 0 05 Feb 2020
Stochastic Approximation versus Sample Average Approximation for population Wasserstein barycenters D. Dvinskikh 199 11 0 21 Jan 2020
Nested-Wasserstein Self-Imitation Learning for Sequence GenerationInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2020 Ruiyi Zhang Changyou Chen Zhe Gan Zheng Wen Wenlin Wang Lawrence Carin 180 7 0 20 Jan 2020
Schrödinger Bridge Samplers Espen Bernton J. Heng Arnaud Doucet Pierre E. Jacob 135 27 0 31 Dec 2019
Algorithm Unrolling: Interpretable, Efficient Deep Learning for Signal and Image ProcessingIEEE Signal Processing Magazine (IEEE SPM), 2019 V. Monga Yuelong Li Yonina C. Eldar 296 1,204 0 22 Dec 2019
Informative GANs via Structured Regularization of Optimal Transport Pierre Bréchet Tao Wu Thomas Möllenhoff Zorah Lähner OT 66 0 0 04 Dec 2019
Ground Metric Learning on GraphsJournal of Mathematical Imaging and Vision (JMIV), 2019 Matthieu Heitz Nicolas Bonneel D. Coeurjolly Marco Cuturi Gabriel Peyré OT 245 22 0 08 Nov 2019
Unsupervised Hierarchy Matching with Optimal Transport over Hyperbolic SpacesInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2019 David Alvarez-Melis Youssef Mroueh Tommi Jaakkola OT 196 26 0 06 Nov 2019
Alleviating Label Switching with Optimal TransportNeural Information Processing Systems (NeurIPS), 2019 Pierre Monteiller Sebastian Claici Edward Chien F. Mirzazadeh Justin Solomon Mikhail Yurochkin 190 6 0 05 Nov 2019
Multi-marginal Wasserstein GANNeural Information Processing Systems (NeurIPS), 2019 Jingyun Liang Langyuan Mo Yifan Zhang Kui Jia Chunhua Shen Zhuliang Yu 153 85 0 03 Nov 2019
Sinkhorn Divergences for Unbalanced Optimal Transport Thibault Séjourné Jean Feydy Franccois-Xavier Vialard A. Trouvé Gabriel Peyré OT 301 82 0 28 Oct 2019
Zero-Shot Recognition via Optimal Transport Wenlin Wang Hongteng Xu Guoyin Wang Wenqi Wang Lawrence Carin OT 132 2 0 20 Oct 2019
Differentiable Deep Clustering with Cluster Size Constraints Aude Genevay Gabriel Dulac-Arnold Jean-Philippe Vert 155 42 0 20 Oct 2019
Quantitative stability of optimal transport maps and linearization of the 2-Wasserstein spaceInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2019 Q. Mérigot Alex Delalande Frédéric Chazal OT 125 49 0 14 Oct 2019
Prescribed Generative Adversarial Networks Adji Bousso Dieng Francisco J. R. Ruiz David M. Blei Michalis K. Titsias GAN DRL 171 61 0 09 Oct 2019
Learning with minibatch Wasserstein : asymptotic and gradient propertiesInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2019 Kilian Fatras Younes Zine Rémi Flamary Rémi Gribonval Nicolas Courty OT 218 102 0 09 Oct 2019
How Well Do WGANs Estimate the Wasserstein Metric? Anton Mallasto Guido Montúfar Augusto Gerolin 89 26 0 09 Oct 2019
Spatio-Temporal Alignments: Optimal transport through space and timeInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2019 H. Janati Marco Cuturi Alexandre Gramfort OT AI4TS 232 35 0 09 Oct 2019
A mathematical theory of cooperative communicationNeural Information Processing Systems (NeurIPS), 2019 Pei Wang Junqi Wang P. Paranamana Patrick Shafto 130 52 0 07 Oct 2019
On the estimation of the Wasserstein distance in generative modelsGerman Conference on Pattern Recognition (DAGM), 2019 Thomas Pinetz Daniel Soukup Thomas Pock GAN 120 9 0 02 Oct 2019
Learning transport cost from subset correspondenceInternational Conference on Learning Representations (ICLR), 2019 Ruishan Liu Akshay Balsubramani James Zou OT 139 16 0 29 Sep 2019
UNITER: UNiversal Image-TExt Representation LearningEuropean Conference on Computer Vision (ECCV), 2019 Yen-Chun Chen Linjie Li Licheng Yu Ahmed El Kholy Faisal Ahmed Zhe Gan Yu Cheng Jingjing Liu VLM OT 309 463 0 25 Sep 2019
Enhancing Traffic Scene Predictions with Generative Adversarial NetworksInternational Conference on Intelligent Transportation Systems (ITSC), 2019 Peter König Sandra Aigner Marco Körner 64 3 0 24 Sep 2019
Estimation of Wasserstein distances in the Spiked Transport ModelBernoulli (Bernoulli), 2019 Jonathan Niles-Weed Philippe Rigollet 158 109 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 214 450 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 235 57 0 02 Aug 2019
Defense Against Adversarial Attacks Using Feature Scattering-based Adversarial TrainingNeural Information Processing Systems (NeurIPS), 2019 Haichao Zhang Jianyu Wang AAML 316 239 0 24 Jul 2019
Optimal Transport-based Alignment of Learned Character Representations for String SimilarityAnnual Meeting of the Association for Computational Linguistics (ACL), 2019 Derek Tam Nicholas Monath Ari Kobren Aaron Traylor Rajarshi Das Andrew McCallum 114 16 0 23 Jul 2019
Statistical data analysis in the Wasserstein spaceESAIM Proceedings and Surveys (ESAIM Proc. Surv.), 2019 Jérémie Bigot 215 36 0 19 Jul 2019
k-GANs: Ensemble of Generative Models with Semi-Discrete Optimal Transport L. Ambrogioni Umut Güçlü Marcel van Gerven GAN 70 4 0 09 Jul 2019
Adversarial Computation of Optimal Transport Maps Jacob Leygonie Jennifer She Amjad Almahairi Sai Rajeswar Aaron Courville GAN OT 123 21 0 24 Jun 2019
GAIT: A Geometric Approach to Information TheoryInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2019 Jose Gallego-Posada Ankit Vani Max Schwarzer Damien Scieur 170 8 0 19 Jun 2019
Minimum Stein Discrepancy EstimatorsNeural Information Processing Systems (NeurIPS), 2019 Alessandro Barp François‐Xavier Briol Andrew B. Duncan Mark Girolami Lester W. Mackey 239 96 0 19 Jun 2019
Local Bures-Wasserstein Transport: A Practical and Fast Mapping Approximation Andrés Hoyos-Idrobo OT 71 0 0 19 Jun 2019
Statistical Inference for Generative Models with Maximum Mean Discrepancy François‐Xavier Briol Alessandro Barp Andrew B. Duncan Mark Girolami 167 78 0 13 Jun 2019
Asymptotic Guarantees for Learning Generative Models with the Sliced-Wasserstein DistanceNeural Information Processing Systems (NeurIPS), 2019 Kimia Nadjahi Alain Durmus Umut Simsekli Roland Badeau MedIm 168 65 0 11 Jun 2019
Maximum Mean Discrepancy Gradient FlowNeural Information Processing Systems (NeurIPS), 2019 Michael Arbel Anna Korba Adil Salim Arthur Gretton 299 179 0 11 Jun 2019
A gradual, semi-discrete approach to generative network training via explicit Wasserstein minimizationInternational Conference on Machine Learning (ICML), 2019 Yucheng Chen Matus Telgarsky Chao Zhang Bolton Bailey Daniel J. Hsu Jian-wei Peng GAN OT 117 22 0 08 Jun 2019
GOT: An Optimal Transport framework for Graph comparisonNeural Information Processing Systems (NeurIPS), 2019 Hermina Petric Maretic Mireille El Gheche Giovanni Chierchia P. Frossard OT 332 131 0 05 Jun 2019
Sinkhorn Barycenters with Free Support via Frank-Wolfe AlgorithmNeural Information Processing Systems (NeurIPS), 2019 Giulia Luise Saverio Salzo Massimiliano Pontil C. Ciliberto 151 69 0 30 May 2019
Statistical bounds for entropic optimal transport: sample complexity and the central limit theoremNeural Information Processing Systems (NeurIPS), 2019 Gonzalo E. Mena Jonathan Niles-Weed OT 218 180 0 28 May 2019
Utility/Privacy Trade-off through the lens of Optimal TransportInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2019 Etienne Boursier Vianney Perchet 258 8 0 27 May 2019
Subspace Detours: Building Transport Plans that are Optimal on Subspace ProjectionsNeural Information Processing Systems (NeurIPS), 2019 Boris Muzellec Marco Cuturi OT 259 33 0 24 May 2019
Geometric Losses for Distributional LearningInternational Conference on Machine Learning (ICML), 2019 A. Mensch Mathieu Blondel Gabriel Peyré 214 16 0 15 May 2019
Minimax estimation of smooth optimal transport maps Jan-Christian Hütter Philippe Rigollet OT 223 29 0 14 May 2019
Learning Generative Models across Incomparable SpacesInternational Conference on Machine Learning (ICML), 2019 Charlotte Bunne David Alvarez-Melis Andreas Krause Stefanie Jegelka GAN 144 117 0 14 May 2019