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Learning Generative Models with Sinkhorn Divergences

1 June 2017

Papers citing "Learning Generative Models with Sinkhorn Divergences"

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Title
Partial Wasserstein and Maximum Mean Discrepancy distances for bridging the gap between outlier detection and drift detection T. Viehmann 23 5 0 09 Jun 2021
Neural Monge Map estimation and its applications JiaoJiao Fan Shu Liu Shaojun Ma Haomin Zhou Yongxin Chen OT 120 27 0 07 Jun 2021
k-Mixup Regularization for Deep Learning via Optimal Transport Kristjan Greenewald Anming Gu Mikhail Yurochkin Justin Solomon Edward Chien 108 19 0 05 Jun 2021
A Survey on Optimal Transport for Machine Learning: Theory and Applications Luis Caicedo Torres Luiz Manella Pereira M. Amini OOD OT 91 47 0 03 Jun 2021
MICo: Improved representations via sampling-based state similarity for Markov decision processes Pablo Samuel Castro Tyler Kastner Prakash Panangaden Mark Rowland 89 39 0 03 Jun 2021
Optimizing Functionals on the Space of Probabilities with Input Convex Neural Networks David Alvarez-Melis Yair Schiff Youssef Mroueh 109 57 0 01 Jun 2021
Diffusion Schrödinger Bridge with Applications to Score-Based Generative Modeling Valentin De Bortoli James Thornton J. Heng Arnaud Doucet DiffM OT 194 477 0 01 Jun 2021
Re-evaluating Word Mover's Distance Ryoma Sato M. Yamada H. Kashima 114 24 0 30 May 2021
Learning High-Dimensional Distributions with Latent Neural Fokker-Planck Kernels Yufan Zhou Changyou Chen Jinhui Xu 39 2 0 10 May 2021
Finite sample approximations of exact and entropic Wasserstein distances between covariance operators and Gaussian processes H. Q. Minh 46 2 0 26 Apr 2021
Fast ABC with joint generative modelling and subset simulation Eliane Maalouf D. Ginsbourger N. Linde 65 0 0 16 Apr 2021
Landmarks Augmentation with Manifold-Barycentric Oversampling Iaroslav Bespalov N. Buzun Oleg Kachan Dmitry V. Dylov MedIm 60 4 0 02 Apr 2021
AlignMixup: Improving Representations By Interpolating Aligned Features Shashanka Venkataramanan Ewa Kijak Laurent Amsaleg Yannis Avrithis WSOL 101 61 0 29 Mar 2021
Semi-Discrete Optimal Transport: Hardness, Regularization and Numerical Solution Bahar Taşkesen Soroosh Shafieezadeh-Abadeh Daniel Kuhn OT 59 26 0 10 Mar 2021
Unbalanced minibatch Optimal Transport; applications to Domain Adaptation Kilian Fatras Thibault Séjourné Nicolas Courty Rémi Flamary OT 88 151 0 05 Mar 2021
Wasserstein GANs Work Because They Fail (to Approximate the Wasserstein Distance) Jan Stanczuk Christian Etmann L. Kreusser Carola-Bibiane Schönlieb GAN 106 48 0 02 Mar 2021
Manifold optimization for non-linear optimal transport problems Bamdev Mishra N. Satyadev Hiroyuki Kasai Pratik Jawanpuria OT 81 11 0 01 Mar 2021
Mitigating Domain Mismatch in Face Recognition Using Style Matching Chun-Hsien Lin Bing-Fei Wu CVBM 58 3 0 26 Feb 2021
Diffusion Earth Mover's Distance and Distribution Embeddings Alexander Tong G. Huguet A. Natik Kincaid MacDonald Manik Kuchroo Ronald R. Coifman Guy Wolf Smita Krishnaswamy MedIm 66 30 0 25 Feb 2021
Improving Approximate Optimal Transport Distances using Quantization Gaspard Beugnot Aude Genevay Kristjan Greenewald Justin Solomon OT MQ 355 11 0 25 Feb 2021
Learning to Generate Wasserstein Barycenters Julien Lacombe Julie Digne Nicolas Courty Nicolas Bonneel 61 12 0 24 Feb 2021
Differentiable Particle Filtering via Entropy-Regularized Optimal Transport Adrien Corenflos James Thornton George Deligiannidis Arnaud Doucet OT 100 70 0 15 Feb 2021
Sliced Multi-Marginal Optimal Transport Samuel N. Cohen Alexander Terenin Yannik Pitcan Brandon Amos M. Deisenroth K. S. S. Kumar OT 39 9 0 14 Feb 2021
On Robust Optimal Transport: Computational Complexity and Barycenter Computation Khang Le Huy Le Nguyen Quang H. Nguyen Tung Pham Hung Bui Nhat Ho OT 82 38 0 13 Feb 2021
Two-sample Test with Kernel Projected Wasserstein Distance Jie Wang Rui Gao Yao Xie 84 20 0 12 Feb 2021
Unsupervised Ground Metric Learning using Wasserstein Singular Vectors Geert-Jan Huizing Laura Cantini Gabriel Peyré SSL OT 62 6 0 11 Feb 2021
On Transportation of Mini-batches: A Hierarchical Approach Khai Nguyen Dang Nguyen Quoc Nguyen Tung Pham Hung Bui Dinh Q. Phung Trung Le Nhat Ho OT 102 18 0 11 Feb 2021
On the Existence of Optimal Transport Gradient for Learning Generative Models Antoine Houdard Arthur Leclaire Nicolas Papadakis Julien Rabin OT GAN 64 6 0 10 Feb 2021
Conditional Loss and Deep Euler Scheme for Time Series Generation Carl Remlinger Joseph Mikael Romuald Elie DiffM 111 12 0 10 Feb 2021
Estimating 2-Sinkhorn Divergence between Gaussian Processes from Finite-Dimensional Marginals Anton Mallasto OT 46 1 0 05 Feb 2021
Optimal Transport as a Defense Against Adversarial Attacks Quentin Bouniot Romaric Audigier Angélique Loesch AAML OOD 32 9 0 05 Feb 2021
Learning High Dimensional Wasserstein Geodesics Shu Liu Shaojun Ma Yongxin Chen H. Zha Haomin Zhou 87 8 0 05 Feb 2021
A Dimension-free Computational Upper-bound for Smooth Optimal Transport Estimation A. Vacher Boris Muzellec Alessandro Rudi Francis R. Bach François-Xavier Vialard OT 77 28 0 13 Jan 2021
Minibatch optimal transport distances; analysis and applications Kilian Fatras Younes Zine Szymon Majewski Rémi Flamary Rémi Gribonval Nicolas Courty OT 116 60 0 05 Jan 2021
Convergence and finite sample approximations of entropic regularized Wasserstein distances in Gaussian and RKHS settings M. H. Quang 111 5 0 05 Jan 2021
Exploiting Chain Rule and Bayes' Theorem to Compare Probability Distributions Huangjie Zheng Mingyuan Zhou OT 163 29 0 28 Dec 2020
Generative Learning With Euler Particle Transport Yuan Gao Jian Huang Yuling Jiao Jin Liu Xiliang Lu J. Yang OT 60 2 0 11 Dec 2020
Model Compression Using Optimal Transport Suhas Lohit Michael J. Jones 81 8 0 07 Dec 2020
Aligning Hyperbolic Representations: an Optimal Transport-based approach Andrés Hoyos-Idrobo OT 61 8 0 02 Dec 2020
Entropic regularization of Wasserstein distance between infinite-dimensional Gaussian measures and Gaussian processes M. H. Quang 72 13 0 15 Nov 2020
A contribution to Optimal Transport on incomparable spaces Titouan Vayer OT 73 20 0 09 Nov 2020
Sinkhorn Natural Gradient for Generative Models Zebang Shen Zhenfu Wang Alejandro Ribeiro Hamed Hassani GAN DiffM 61 12 0 09 Nov 2020
Efficient Robust Optimal Transport with Application to Multi-Label Classification Pratik Jawanpuria N. Satyadev Bamdev Mishra OT 69 3 0 22 Oct 2020
Statistical guarantees for generative models without domination Nicolas Schreuder Victor-Emmanuel Brunel A. Dalalyan GAN 127 35 0 19 Oct 2020
Differentiable Divergences Between Time Series Mathieu Blondel A. Mensch Jean-Philippe Vert AI4TS 136 39 0 16 Oct 2020
Improving Text Generation with Student-Forcing Optimal Transport Guoyin Wang Chunyuan Li Jianqiao Li Hao Fu Yuh-Chen Lin ... Ruiyi Zhang Wenlin Wang Dinghan Shen Qian Yang Lawrence Carin OT 78 18 0 12 Oct 2020
Learning Deep-Latent Hierarchies by Stacking Wasserstein Autoencoders Benoit Gaujac Ilya Feige David Barber DiffM BDL 62 0 0 07 Oct 2020
Unpaired Deep Learning for Accelerated MRI using Optimal Transport Driven CycleGAN Gyutaek Oh Byeongsu Sim Hyungjin Chung Leonard Sunwoo J. C. Ye OOD MedIm 78 71 0 29 Aug 2020
Quantum versus Classical Generative Modelling in Finance Brian Coyle Maxwell P. Henderson Justin Chan Jin Le N. Kumar M. Paini E. Kashefi 51 59 0 03 Aug 2020
Generalization Properties of Optimal Transport GANs with Latent Distribution Learning Giulia Luise Massimiliano Pontil C. Ciliberto GAN OT 66 22 0 29 Jul 2020