Posterior Sampling Based on Gradient Flows of the MMD with Negative Distance Kernel

4 October 2023

Papers citing "Posterior Sampling Based on Gradient Flows of the MMD with Negative Distance Kernel"

21 / 21 papers shown

Title
Slicing the Gaussian Mixture Wasserstein Distance Moritz Piening Robert Beinert 31 0 0 11 Apr 2025
Smoothed Distance Kernels for MMDs and Applications in Wasserstein Gradient Flows Nicolaj Rux Michael Quellmalz Gabriele Steidl 22 0 0 10 Apr 2025
DDEQs: Distributional Deep Equilibrium Models through Wasserstein Gradient Flows Jonathan Geuter Clément Bonet Anna Korba David Alvarez-Melis 54 0 0 03 Mar 2025
Contextual Scenario Generation for Two-Stage Stochastic Programming David Islip Roy H. Kwon Sanghyeon Bae Woo Chang Kim 49 0 0 07 Feb 2025
Inclusive KL Minimization: A Wasserstein-Fisher-Rao Gradient Flow Perspective Jia-Jie Zhu 66 1 0 31 Oct 2024
Conditional Generative Models for Contrast-Enhanced Synthesis of T1w and T1 Maps in Brain MRI Moritz Piening Fabian Altekrüger Gabriele Steidl Elke Hattingen Eike Steidl MedIm 24 0 0 11 Oct 2024
Fast Summation of Radial Kernels via QMC Slicing Johannes Hertrich Tim Jahn Michael Quellmalz 16 5 0 02 Oct 2024
Wasserstein Gradient Flows of MMD Functionals with Distance Kernel and Cauchy Problems on Quantile Functions Richard Duong Viktor Stein Robert Beinert J. Hertrich Gabriele Steidl 28 2 0 14 Aug 2024
Importance Corrected Neural JKO Sampling Johannes Hertrich Robert Gruhlke 26 1 0 29 Jul 2024
Rethinking the Diffusion Models for Numerical Tabular Data Imputation from the Perspective of Wasserstein Gradient Flow Zhichao Chen Haoxuan Li Fangyikang Wang Odin Zhang Hu Xu Xiaoyu Jiang Zhihuan Song Eric H. Wang DiffM 37 1 0 22 Jun 2024
Deep MMD Gradient Flow without adversarial training Alexandre Galashov Valentin De Bortoli Arthur Gretton DiffM 27 7 0 10 May 2024
Conditional Wasserstein Distances with Applications in Bayesian OT Flow Matching Jannis Chemseddine Paul Hagemann Gabriele Steidl Christian Wald 38 9 0 27 Mar 2024
Mixed Noise and Posterior Estimation with Conditional DeepGEM Paul Hagemann J. Hertrich Maren Casfor Sebastian Heidenreich Gabriele Steidl 14 0 0 05 Feb 2024
Fast Kernel Summation in High Dimensions via Slicing and Fourier Transforms Johannes Hertrich 18 7 0 16 Jan 2024
Learning from small data sets: Patch-based regularizers in inverse problems for image reconstruction Moritz Piening Fabian Altekrüger J. Hertrich Paul Hagemann Andrea Walther Gabriele Steidl 19 5 0 27 Dec 2023
Y-Diagonal Couplings: Approximating Posteriors with Conditional Wasserstein Distances Jannis Chemseddine Paul Hagemann Christian Wald 24 3 0 20 Oct 2023
Minimizing $f$ -Divergences by Interpolating Velocity Fields Song Liu Jiahao Yu J. Simons Mingxuan Yi Mark Beaumont 10 2 0 24 May 2023
Nonparametric Generative Modeling with Conditional Sliced-Wasserstein Flows Chao Du Tianbo Li Tianyu Pang Shuicheng Yan Min-Bin Lin DiffM BDL 38 12 0 03 May 2023
Bayesian Posterior Perturbation Analysis with Integral Probability Metrics A. Garbuno-Iñigo T. Helin Franca Hoffmann Bamdad Hosseini 23 9 0 02 Mar 2023
Functional Generalized Empirical Likelihood Estimation for Conditional Moment Restrictions Heiner Kremer Jia-Jie Zhu Krikamol Muandet Bernhard Schölkopf 27 8 0 11 Jul 2022
Variational Wasserstein gradient flow JiaoJiao Fan Qinsheng Zhang Amirhossein Taghvaei Yongxin Chen 68 54 0 04 Dec 2021