From optimal transport to generative modeling: the VEGAN cookbook

22 May 2017

Olivier Bousquet

Sylvain Gelly

Ilya O. Tolstikhin

Carl-Johann Simon-Gabriel

B. Schoelkopf

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Papers citing "From optimal transport to generative modeling: the VEGAN cookbook"

23 / 23 papers shown

Title
A Review of Bayesian Uncertainty Quantification in Deep Probabilistic Image Segmentation M. Valiuddin R. V. Sloun C.G.A. Viviers Peter H. N. de With Fons van der Sommen UQCV 89 1 0 25 Nov 2024
Imitation from Diverse Behaviors: Wasserstein Quality Diversity Imitation Learning with Single-Step Archive Exploration Xingrui Yu Zhenglin Wan David Mark Bossens Yueming Lyu Qing-Wu Guo Ivor W. Tsang 127 0 0 11 Nov 2024
Accelerating Sinkhorn Algorithm with Sparse Newton Iterations Xun Tang Michael Shavlovsky Holakou Rahmanian Elisa Tardini K. K. Thekumparampil Tesi Xiao Lexing Ying OT 33 4 0 20 Jan 2024
Differentially Private Gradient Flow based on the Sliced Wasserstein Distance Ilana Sebag Muni Sreenivas Pydi Jean-Yves Franceschi Alain Rakotomamonjy Mike Gartrell Jamal Atif Alexandre Allauzen 24 2 0 13 Dec 2023
On Certified Generalization in Structured Prediction Bastian Boll Christoph Schnörr 21 0 0 15 Jun 2023
The Monge Gap: A Regularizer to Learn All Transport Maps Théo Uscidda Marco Cuturi OT 50 26 0 09 Feb 2023
Auto-Encoding Goodness of Fit A. Palmer Zhiyi Chi Derek Aguiar J. Bi 35 1 0 12 Oct 2022
InfoOT: Information Maximizing Optimal Transport Ching-Yao Chuang Stefanie Jegelka David Alvarez-Melis OT 35 12 0 06 Oct 2022
Don't Generate Me: Training Differentially Private Generative Models with Sinkhorn Divergence Tianshi Cao Alex Bie Arash Vahdat Sanja Fidler Karsten Kreis SyDa DiffM 11 71 0 01 Nov 2021
Learning and Inference in Imaginary Noise Models Saeed Saremi BDL DRL 6 2 0 18 May 2020
Physarum Powered Differentiable Linear Programming Layers and Applications Zihang Meng Sathya Ravi Vikas Singh 19 5 0 30 Apr 2020
Statistical and Topological Properties of Sliced Probability Divergences Kimia Nadjahi Alain Durmus Lénaïc Chizat Soheil Kolouri Shahin Shahrampour Umut Simsekli 24 80 0 12 Mar 2020
Rate-Regularization and Generalization in VAEs Alican Bozkurt Babak Esmaeili Jean-Baptiste Tristan Dana H. Brooks Jennifer G. Dy Jan Willem van de Meent DRL 22 7 0 11 Nov 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 16 17 0 08 Jun 2019
Deep Generative Learning via Variational Gradient Flow Yuan Gao Yuling Jiao Yang Wang Yao Wang Can Yang Shunkang Zhang 19 36 0 24 Jan 2019
Conditional deep surrogate models for stochastic, high-dimensional, and multi-fidelity systems Yibo Yang P. Perdikaris SyDa BDL AI4CE 21 55 0 15 Jan 2019
Towards Optimal Transport with Global Invariances David Alvarez-Melis Stefanie Jegelka Tommi Jaakkola OT 20 71 0 25 Jun 2018
Sliced-Wasserstein Flows: Nonparametric Generative Modeling via Optimal Transport and Diffusions Antoine Liutkus Umut Simsekli Szymon Majewski Alain Durmus Fabian-Robert Stöter DiffM 32 119 0 21 Jun 2018
Autoregressive Quantile Networks for Generative Modeling Georg Ostrovski Will Dabney Rémi Munos DRL 20 85 0 14 Jun 2018
Deep Generative Models in the Real-World: An Open Challenge from Medical Imaging Xiaoran Chen Nick Pawlowski Martin Rajchl Ben Glocker E. Konukoglu OOD MedIm 19 49 0 14 Jun 2018
A unified framework for hard and soft clustering with regularized optimal transport Jean-Frédéric Diebold Nicolas Papadakis Arnaud Dessein Charles-Alban Deledalle FedML 47 9 0 12 Nov 2017
GAN and VAE from an Optimal Transport Point of View Aude Genevay Gabriel Peyré Marco Cuturi OT DRL 26 62 0 06 Jun 2017
Learning Generative Models with Sinkhorn Divergences Aude Genevay Gabriel Peyré Marco Cuturi OT 39 617 0 01 Jun 2017