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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 / 399 papers shown

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Embedding Signals on Knowledge Graphs with Unbalanced Diffusion Earth Mover's DistanceIEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2021 Alexander Tong G. Huguet Dennis L. Shung A. Natik Manik Kuchroo Guillaume Lajoie Guy Wolf Smita Krishnaswamy 135 9 0 26 Jul 2021
AASAE: Augmentation-Augmented Stochastic Autoencoders William Falcon A. Jha Teddy Koker Dong Wang 157 1 0 26 Jul 2021
Optimal transport-based machine learning to match specific patterns: application to the detection of molecular regulation patterns in omics data T. Nguyen Warith Harchaoui Lucile Mégret Cloé Mendoza Olivier Bouaziz C. Néri Antoine Chambaz 118 1 0 21 Jul 2021
Scalable Optimal Transport in High Dimensions for Graph Distances, Embedding Alignment, and MoreInternational Conference on Machine Learning (ICML), 2021 Johannes Klicpera Marten Lienen Stephan Günnemann OT 171 14 0 14 Jul 2021
Hidden Convexity of Wasserstein GANs: Interpretable Generative Models with Closed-Form Solutions Arda Sahiner Tolga Ergen Batu Mehmet Ozturkler Burak Bartan John M. Pauly Morteza Mardani Mert Pilanci GAN 299 21 0 12 Jul 2021
A stochastic Gauss-Newton algorithm for regularized semi-discrete optimal transport Bernard Bercu Jérémie Bigot S. Gadat Emilia Siviero 239 7 0 12 Jul 2021
Direct Measure Matching for Crowd Counting Hui Lin Xiaopeng Hong Zhiheng Ma Xing Wei Yunfeng Qiu Yaowei Wang Yihong Gong OT 135 48 0 04 Jul 2021
Deep Inertial Navigation using Continuous Domain Adaptation and Optimal Transport Mohammed Alloulah Maximilian Arnold Anton Isopoussu OOD 134 2 0 29 Jun 2021
Asymptotics for semi-discrete entropic optimal transportSIAM Journal on Mathematical Analysis (SIAM J. Math. Anal.), 2021 Jason M. Altschuler Jonathan Niles-Weed Austin J. Stromme 116 33 0 22 Jun 2021
Discrepancy-based Inference for Intractable Generative Models using Quasi-Monte CarloElectronic Journal of Statistics (EJS), 2021 Ziang Niu J. Meier F. Briol 298 13 0 22 Jun 2021
Manifold Matching via Deep Metric Learning for Generative ModelingIEEE International Conference on Computer Vision (ICCV), 2021 Mengyu Dai Haibin Hang GAN 150 12 0 20 Jun 2021
KALE Flow: A Relaxed KL Gradient Flow for Probabilities with Disjoint Support Pierre Glaser Michael Arbel Arthur Gretton 217 39 0 16 Jun 2021
Non-asymptotic convergence bounds for Wasserstein approximation using point cloudsNeural Information Processing Systems (NeurIPS), 2021 Q. Mérigot F. Santambrogio Clément Sarrazin 68 33 0 15 Jun 2021
Learning Revenue-Maximizing Auctions With Differentiable MatchingInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2021 Michael J. Curry Uro Lyi Tom Goldstein John P. Dickerson 158 22 0 15 Jun 2021
A Wasserstein Minimax Framework for Mixed Linear RegressionInternational Conference on Machine Learning (ICML), 2021 Theo Diamandis Yonina C. Eldar Alireza Fallah Farzan Farnia Asuman Ozdaglar 163 7 0 14 Jun 2021
Separation Results between Fixed-Kernel and Feature-Learning Probability MetricsNeural Information Processing Systems (NeurIPS), 2021 Carles Domingo-Enrich Youssef Mroueh 185 1 0 10 Jun 2021
Conditional COT-GAN for Video Prediction with Kernel Smoothing Tianlin Xu Beatrice Acciaio GAN AI4TS CML 103 6 0 10 Jun 2021
Partial Wasserstein and Maximum Mean Discrepancy distances for bridging the gap between outlier detection and drift detection T. Viehmann 69 8 0 09 Jun 2021
Neural Monge Map estimation and its applications JiaoJiao Fan Shu Liu Shaojun Ma Haomin Zhou Yongxin Chen OT 318 32 0 07 Jun 2021
k-Mixup Regularization for Deep Learning via Optimal Transport Kristjan Greenewald Anming Gu Mikhail Yurochkin Justin Solomon Edward Chien 240 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 177 56 0 03 Jun 2021
MICo: Improved representations via sampling-based state similarity for Markov decision processesNeural Information Processing Systems (NeurIPS), 2021 Pablo Samuel Castro Tyler Kastner Prakash Panangaden Mark Rowland 403 43 0 03 Jun 2021
Optimizing Functionals on the Space of Probabilities with Input Convex Neural Networks David Alvarez-Melis Yair Schiff Youssef Mroueh 272 63 0 01 Jun 2021
Diffusion Schrödinger Bridge with Applications to Score-Based Generative ModelingNeural Information Processing Systems (NeurIPS), 2021 Valentin De Bortoli James Thornton J. Heng Arnaud Doucet DiffM OT 527 594 0 01 Jun 2021
Re-evaluating Word Mover's DistanceInternational Conference on Machine Learning (ICML), 2021 Ryoma Sato M. Yamada H. Kashima 376 25 0 30 May 2021
Learning High-Dimensional Distributions with Latent Neural Fokker-Planck Kernels Jiuxiang Gu Changyou Chen Jinhui Xu 188 2 0 10 May 2021
Finite sample approximations of exact and entropic Wasserstein distances between covariance operators and Gaussian processes H. Q. Minh 204 3 0 26 Apr 2021
Fast ABC with joint generative modelling and subset simulationInternational Conference on Machine Learning, Optimization, and Data Science (MOD), 2021 Eliane Maalouf D. Ginsbourger N. Linde 176 0 0 16 Apr 2021
Landmarks Augmentation with Manifold-Barycentric OversamplingIEEE Access (IEEE Access), 2021 Iaroslav Bespalov N. Buzun Oleg Kachan Dmitry V. Dylov MedIm 171 4 0 02 Apr 2021
AlignMixup: Improving Representations By Interpolating Aligned FeaturesComputer Vision and Pattern Recognition (CVPR), 2021 Shashanka Venkataramanan Ewa Kijak Laurent Amsaleg Yannis Avrithis WSOL 254 73 0 29 Mar 2021
Semi-Discrete Optimal Transport: Hardness, Regularization and Numerical SolutionMathematical programming (Math. Program.), 2021 Bahar Taşkesen Soroosh Shafieezadeh-Abadeh Daniel Kuhn OT 218 35 0 10 Mar 2021
Unbalanced minibatch Optimal Transport; applications to Domain AdaptationInternational Conference on Machine Learning (ICML), 2021 Kilian Fatras Thibault Séjourné Nicolas Courty Rémi Flamary OT 176 174 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 285 52 0 02 Mar 2021
Manifold optimization for non-linear optimal transport problems Bamdev Mishra N. Satyadev Hiroyuki Kasai Pratik Jawanpuria OT 193 12 0 01 Mar 2021
Mitigating Domain Mismatch in Face Recognition Using Style MatchingNeurocomputing (Neurocomputing), 2021 Chun-Hsien Lin Bing-Fei Wu CVBM 154 4 0 26 Feb 2021
Diffusion Earth Mover's Distance and Distribution EmbeddingsInternational Conference on Machine Learning (ICML), 2021 Alexander Tong G. Huguet A. Natik Kincaid MacDonald Manik Kuchroo Ronald R. Coifman Guy Wolf Smita Krishnaswamy MedIm 127 32 0 25 Feb 2021
Improving Approximate Optimal Transport Distances using QuantizationConference on Uncertainty in Artificial Intelligence (UAI), 2021 Gaspard Beugnot Aude Genevay Kristjan Greenewald Justin Solomon OT MQ 577 11 0 25 Feb 2021
Learning to Generate Wasserstein BarycentersJournal of Mathematical Imaging and Vision (JMIV), 2021 Julien Lacombe Julie Digne Nicolas Courty Nicolas Bonneel 111 12 0 24 Feb 2021
Differentiable Particle Filtering via Entropy-Regularized Optimal TransportInternational Conference on Machine Learning (ICML), 2021 Adrien Corenflos James Thornton George Deligiannidis Arnaud Doucet OT 209 86 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 137 9 0 14 Feb 2021
On Robust Optimal Transport: Computational Complexity and Barycenter ComputationNeural Information Processing Systems (NeurIPS), 2021 Khang Le Huy Le Nguyen Quang H. Nguyen Tung Pham Hung Bui Nhat Ho OT 163 41 0 13 Feb 2021
Two-sample Test with Kernel Projected Wasserstein DistanceInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2021 Jie Wang Rui Gao Yao Xie 296 22 0 12 Feb 2021
Unsupervised Ground Metric Learning using Wasserstein Singular VectorsInternational Conference on Machine Learning (ICML), 2021 Geert-Jan Huizing Laura Cantini Gabriel Peyré SSL OT 184 8 0 11 Feb 2021
On Transportation of Mini-batches: A Hierarchical ApproachInternational Conference on Machine Learning (ICML), 2021 Khai Nguyen Dang Nguyen Quoc Nguyen Tung Pham Hung Bui Dinh Q. Phung Trung Le Nhat Ho OT 190 19 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 126 7 0 10 Feb 2021
Conditional Loss and Deep Euler Scheme for Time Series GenerationAAAI Conference on Artificial Intelligence (AAAI), 2021 Carl Remlinger Joseph Mikael Romuald Elie DiffM 275 15 0 10 Feb 2021
Estimating 2-Sinkhorn Divergence between Gaussian Processes from Finite-Dimensional Marginals Anton Mallasto OT 117 1 0 05 Feb 2021
Optimal Transport as a Defense Against Adversarial AttacksInternational Conference on Pattern Recognition (ICPR), 2021 Quentin Bouniot Romaric Audigier Angélique Loesch AAML OOD 89 9 0 05 Feb 2021
Learning High Dimensional Wasserstein Geodesics Shu Liu Shaojun Ma Yongxin Chen H. Zha Haomin Zhou 273 10 0 05 Feb 2021
A Dimension-free Computational Upper-bound for Smooth Optimal Transport EstimationAnnual Conference Computational Learning Theory (COLT), 2021 A. Vacher Boris Muzellec Alessandro Rudi Francis R. Bach François-Xavier Vialard OT 197 30 0 13 Jan 2021