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Large-Scale Wasserstein Gradient Flows

1 June 2021

Papers citing "Large-Scale Wasserstein Gradient Flows"

50 / 52 papers shown

Title
From Missing Pieces to Masterpieces: Image Completion with Context-Adaptive Diffusion Pourya Shamsolmoali Masoumeh Zareapoor Huiyu Zhou Michael Felsberg Dacheng Tao Xuelong Li DiffM 103 0 0 19 Apr 2025
Diffusion Models for Tabular Data: Challenges, Current Progress, and Future Directions Zhong Li Qi Huang Lincen Yang Jiayang Shi Zhao Yang Niki van Stein Thomas Bäck M. Leeuwen DiffM 118 0 0 24 Feb 2025
Convergence Analysis of the Wasserstein Proximal Algorithm beyond Geodesic Convexity Shuailong Zhu Xiaohui Chen 106 0 0 25 Jan 2025
Computational and Statistical Asymptotic Analysis of the JKO Scheme for Iterative Algorithms to update distributions Shang Wu Yazhen Wang 104 0 0 11 Jan 2025
Non-geodesically-convex optimization in the Wasserstein space Hoang Phuc Hau Luu Hanlin Yu Bernardo Williams Petrus Mikkola Marcelo Hartmann Kai Puolamaki Arto Klami 131 2 0 08 Jan 2025
Local Flow Matching Generative Models Chen Xu Xiuyuan Cheng Yao Xie 132 2 0 03 Jan 2025
Path-Guided Particle-based Sampling Mingzhou Fan Ruida Zhou C. Tian Xiaoning Qian 124 7 0 04 Dec 2024
Stochastic variance-reduced Gaussian variational inference on the Bures-Wasserstein manifold Hoang Phuc Hau Luu Hanlin Yu Bernardo Williams Marcelo Hartmann Arto Klami DRL 151 0 0 03 Oct 2024
Relative-Translation Invariant Wasserstein Distance Binshuai Wang Qiwei Di Ming Yin Mengdi Wang Quanquan Gu Peng Wei 67 0 0 04 Sep 2024
Importance Corrected Neural JKO Sampling Johannes Hertrich Robert Gruhlke 102 2 0 29 Jul 2024
Learning Diffusion at Lightspeed Antonio Terpin Nicolas Lanzetti Florian Dorfler DiffM 105 9 0 18 Jun 2024
Forward-Euler time-discretization for Wasserstein gradient flows can be wrong Yewei Xu Qin Li 87 1 0 12 Jun 2024
Optimal State Estimation in the Presence of Non-Gaussian Uncertainty via Wasserstein Distance Minimization Himanshu Prabhat Raktim Bhattacharya 77 1 0 06 Mar 2024
Scalable Wasserstein Gradient Flow for Generative Modeling through Unbalanced Optimal Transport Jaemoo Choi Jaewoong Choi Myungjoo Kang 127 11 0 08 Feb 2024
Neural Sinkhorn Gradient Flow Huminhao Zhu Fangyikang Wang Chao Zhang Han Zhao Hui Qian 72 8 0 25 Jan 2024
Accelerating Sinkhorn Algorithm with Sparse Newton Iterations Xun Tang Michael Shavlovsky Holakou Rahmanian Elisa Tardini K. K. Thekumparampil Tesi Xiao Lexing Ying OT 61 5 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 109 3 0 13 Dec 2023
Convergence of flow-based generative models via proximal gradient descent in Wasserstein space Xiuyuan Cheng Jianfeng Lu Yixin Tan Yao Xie 201 19 0 26 Oct 2023
A Computational Framework for Solving Wasserstein Lagrangian Flows Kirill Neklyudov Rob Brekelmans Alexander Tong Lazar Atanackovic Qiang Liu Alireza Makhzani OT 106 23 0 16 Oct 2023
Posterior Sampling Based on Gradient Flows of the MMD with Negative Distance Kernel Paul Hagemann J. Hertrich Fabian Altekrüger Robert Beinert Jannis Chemseddine Gabriele Steidl 116 25 0 04 Oct 2023
Generating Synthetic Datasets by Interpolating along Generalized Geodesics JiaoJiao Fan David Alvarez-Melis 104 10 0 12 Jun 2023
Unifying GANs and Score-Based Diffusion as Generative Particle Models Jean-Yves Franceschi Mike Gartrell Ludovic Dos Santos Thibaut Issenhuth Emmanuel de Bezenac Mickaël Chen A. Rakotomamonjy DiffM 97 23 0 25 May 2023
Generative Sliced MMD Flows with Riesz Kernels J. Hertrich Christian Wald Fabian Altekrüger Paul Hagemann 97 27 0 19 May 2023
Wasserstein Gradient Flows for Optimizing Gaussian Mixture Policies Hanna Ziesche Leonel Rozo 72 5 0 17 May 2023
Energy-guided Entropic Neural Optimal Transport Petr Mokrov Alexander Korotin Alexander Kolesov Nikita Gushchin Evgeny Burnaev OT 152 23 0 12 Apr 2023
Generative Modeling with Flow-Guided Density Ratio Learning Alvin Heng Abdul Fatir Ansari Harold Soh 60 1 0 07 Mar 2023
Entropy-dissipation Informed Neural Network for McKean-Vlasov Type PDEs Zebang Shen Zhenfu Wang 104 5 0 11 Feb 2023
Self-Consistent Velocity Matching of Probability Flows Lingxiao Li Samuel Hurault Justin Solomon 108 15 0 31 Jan 2023
Neural Wasserstein Gradient Flows for Maximum Mean Discrepancies with Riesz Kernels Fabian Altekrüger J. Hertrich Gabriele Steidl 79 14 0 27 Jan 2023
Normalizing flow neural networks by JKO scheme Chen Xu Xiuyuan Cheng Yao Xie 107 30 0 29 Dec 2022
Taming Hyperparameter Tuning in Continuous Normalizing Flows Using the JKO Scheme Alexander Vidal Samy Wu Fung Luis Tenorio Stanley Osher L. Nurbekyan 102 20 0 30 Nov 2022
Particle-based Variational Inference with Preconditioned Functional Gradient Flow Hanze Dong Xi Wang Yong Lin Tong Zhang 98 20 0 25 Nov 2022
Proximal Mean Field Learning in Shallow Neural Networks Alexis M. H. Teter Iman Nodozi A. Halder FedML 77 1 0 25 Oct 2022
On amortizing convex conjugates for optimal transport Brandon Amos OT 161 28 0 21 Oct 2022
InfoOT: Information Maximizing Optimal Transport Ching-Yao Chuang Stefanie Jegelka David Alvarez-Melis OT 112 12 0 06 Oct 2022
Batch Bayesian Optimization via Particle Gradient Flows Enrico Crovini S. Cotter K. Zygalakis Andrew B. Duncan 65 3 0 10 Sep 2022
Discrete Langevin Sampler via Wasserstein Gradient Flow Haoran Sun H. Dai Bo Dai Haomin Zhou Dale Schuurmans BDL 90 24 0 29 Jun 2022
Supervised Training of Conditional Monge Maps Charlotte Bunne Andreas Krause Marco Cuturi OT 145 65 0 28 Jun 2022
Meta Optimal Transport Brandon Amos Samuel N. Cohen Giulia Luise I. Redko OT 103 24 0 10 Jun 2022
Self-Consistency of the Fokker-Planck Equation Zebang Shen Zhenfu Wang Satyen Kale Alejandro Ribeiro Aim Karbasi Hamed Hassani 83 21 0 02 Jun 2022
Neural Optimal Transport with General Cost Functionals Arip Asadulaev Alexander Korotin Vage Egiazarian Petr Mokrov Evgeny Burnaev OT 124 34 0 30 May 2022
Learning with Stochastic Orders Carles Domingo-Enrich Yair Schiff Youssef Mroueh 66 2 0 27 May 2022
A Distributed Algorithm for Measure-valued Optimization with Additive Objective Iman Nodozi A. Halder 68 1 0 17 Feb 2022
Understanding DDPM Latent Codes Through Optimal Transport Valentin Khrulkov Gleb Ryzhakov Andrei Chertkov Ivan Oseledets OT DiffM 75 53 0 14 Feb 2022
Wasserstein Iterative Networks for Barycenter Estimation Alexander Korotin Vage Egiazarian Lingxiao Li Evgeny Burnaev 113 30 0 28 Jan 2022
Learning Proximal Operators to Discover Multiple Optima Lingxiao Li Noam Aigerman Vladimir G. Kim Jiajin Li Kristjan Greenewald Mikhail Yurochkin Justin Solomon 94 1 0 28 Jan 2022
Variational Wasserstein gradient flow JiaoJiao Fan Qinsheng Zhang Amirhossein Taghvaei Yongxin Chen 167 57 0 04 Dec 2021
Input Convex Gradient Networks Jack Richter-Powell Jonathan Lorraine Brandon Amos 70 15 0 23 Nov 2021
Efficient Gradient Flows in Sliced-Wasserstein Space Clément Bonet Nicolas Courty Franccois Septier Lucas Drumetz 141 21 0 21 Oct 2021
Proximal Optimal Transport Modeling of Population Dynamics Charlotte Bunne Laetitia Meng-Papaxanthos Andreas Krause Marco Cuturi OT 97 93 0 11 Jun 2021