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Variational Wasserstein gradient flow

4 December 2021

Qinsheng Zhang

Papers citing "Variational Wasserstein gradient flow"

41 / 41 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 146 0 0 19 Apr 2025
DDEQs: Distributional Deep Equilibrium Models through Wasserstein Gradient Flows Jonathan Geuter Clément Bonet Anna Korba David Alvarez-Melis 232 0 0 03 Mar 2025
Towards Understanding Gradient Dynamics of the Sliced-Wasserstein Distance via Critical Point Analysis Christophe Vauthier Anna Korba Quentin Mérigot 97 0 0 10 Feb 2025
Adversarial Transform Particle Filters Chengxin Gong Wei Lin Cheng Zhang 103 0 0 10 Feb 2025
Nested Annealed Training Scheme for Generative Adversarial Networks Chang Wan Ming-Hsuan Yang Minglu Li Yunliang Jiang Zhonglong Zheng GAN 163 1 0 20 Jan 2025
Computational and Statistical Asymptotic Analysis of the JKO Scheme for Iterative Algorithms to update distributions Shang Wu Yazhen Wang 139 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 178 2 0 08 Jan 2025
Functional Gradient Flows for Constrained Sampling Shiyue Zhang Longlin Yu Ziheng Cheng Cheng Zhang 78 0 0 30 Oct 2024
Semi-Implicit Functional Gradient Flow for Efficient Sampling Shiyue Zhang Ziheng Cheng Cheng Zhang 120 0 0 23 Oct 2024
Local Flow Matching Generative Models Chen Xu Xiuyuan Cheng Yao Xie 194 4 0 03 Oct 2024
Relative-Translation Invariant Wasserstein Distance Binshuai Wang Qiwei Di Ming Yin Mengdi Wang Quanquan Gu Peng Wei 105 0 0 04 Sep 2024
Importance Corrected Neural JKO Sampling Johannes Hertrich Robert Gruhlke 160 4 0 29 Jul 2024
A Differential Equation Approach for Wasserstein GANs and Beyond Zachariah Malik Yu-Jui Huang 59 0 0 25 May 2024
Deep MMD Gradient Flow without adversarial training Alexandre Galashov Valentin De Bortoli Arthur Gretton DiffM 121 9 0 10 May 2024
Scalable Wasserstein Gradient Flow for Generative Modeling through Unbalanced Optimal Transport Jaemoo Choi Jaewoong Choi Myungjoo Kang 184 13 0 08 Feb 2024
Neural Sinkhorn Gradient Flow Huminhao Zhu Fangyikang Wang Chao Zhang Han Zhao Hui Qian 97 8 0 25 Jan 2024
Geometry-Aware Normalizing Wasserstein Flows for Optimal Causal Inference Kaiwen Hou 165 0 0 30 Nov 2023
Gaussian Interpolation Flows Yuan Gao Jianxia Huang Yuling Jiao AI4CE 127 8 0 20 Nov 2023
Particle-based Variational Inference with Generalized Wasserstein Gradient Flow Ziheng Cheng Shiyue Zhang Longlin Yu Cheng Zhang BDL 79 10 0 25 Oct 2023
A Computational Framework for Solving Wasserstein Lagrangian Flows Kirill Neklyudov Rob Brekelmans Alexander Tong Lazar Atanackovic Qiang Liu Alireza Makhzani OT 164 25 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 176 26 0 04 Oct 2023
Generating Synthetic Datasets by Interpolating along Generalized Geodesics JiaoJiao Fan David Alvarez-Melis 136 11 0 12 Jun 2023
Push: Concurrent Probabilistic Programming for Bayesian Deep Learning Daniel Huang Christian Camaño Jonathan Tsegaye Jonathan Austin Gale AI4CE 118 0 0 10 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 170 24 0 25 May 2023
Generative Sliced MMD Flows with Riesz Kernels J. Hertrich Christian Wald Fabian Altekrüger Paul Hagemann 139 30 0 19 May 2023
Generative Modeling with Flow-Guided Density Ratio Learning Alvin Heng Abdul Fatir Ansari Harold Soh 95 1 0 07 Mar 2023
Improved dimension dependence of a proximal algorithm for sampling JiaoJiao Fan Bo Yuan Yongxin Chen 147 29 0 20 Feb 2023
Entropy-dissipation Informed Neural Network for McKean-Vlasov Type PDEs Zebang Shen Zhenfu Wang 151 6 0 11 Feb 2023
Self-Consistent Velocity Matching of Probability Flows Lingxiao Li Samuel Hurault Justin Solomon 202 16 0 31 Jan 2023
SAN: Inducing Metrizability of GAN with Discriminative Normalized Linear Layer Yuhta Takida Masaaki Imaizumi Takashi Shibuya Chieh-Hsin Lai Toshimitsu Uesaka Naoki Murata Yuki Mitsufuji GAN 193 16 0 30 Jan 2023
Neural Wasserstein Gradient Flows for Maximum Mean Discrepancies with Riesz Kernels Fabian Altekrüger J. Hertrich Gabriele Steidl 184 14 0 27 Jan 2023
Normalizing flow neural networks by JKO scheme Chen Xu Xiuyuan Cheng Yao Xie 149 32 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 128 21 0 30 Nov 2022
Particle-based Variational Inference with Preconditioned Functional Gradient Flow Hanze Dong Xi Wang Yong Lin Tong Zhang 124 21 0 25 Nov 2022
Entropic Neural Optimal Transport via Diffusion Processes Nikita Gushchin Alexander Kolesov Alexander Korotin Dmitry Vetrov Evgeny Burnaev OT DiffM 155 43 0 02 Nov 2022
Nesterov smoothing for sampling without smoothness JiaoJiao Fan Bo Yuan Jiaming Liang Yongxin Chen 138 2 0 15 Aug 2022
Neural Optimal Transport with General Cost Functionals Arip Asadulaev Alexander Korotin Vage Egiazarian Petr Mokrov Evgeny Burnaev OT 185 34 0 30 May 2022
Efficient Gradient Flows in Sliced-Wasserstein Space Clément Bonet Nicolas Courty Franccois Septier Lucas Drumetz 203 23 0 21 Oct 2021
Neural Monge Map estimation and its applications JiaoJiao Fan Shu Liu Shaojun Ma Haomin Zhou Yongxin Chen OT 138 29 0 07 Jun 2021
Optimizing Functionals on the Space of Probabilities with Input Convex Neural Networks David Alvarez-Melis Yair Schiff Youssef Mroueh 128 60 0 01 Jun 2021
Functional optimal transport: map estimation and domain adaptation for functional data Jiacheng Zhu Aritra Guha Dat Do Mengdi Xu X. Nguyen Ding Zhao OT 135 8 0 07 Feb 2021