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"

24 / 24 papers shown

Title
Fast Summation of Radial Kernels via QMC Slicing Johannes Hertrich Tim Jahn Michael Quellmalz 82 5 0 02 Oct 2024
Importance Corrected Neural JKO Sampling Johannes Hertrich Robert Gruhlke 88 2 0 29 Jul 2024
Generative Sliced MMD Flows with Riesz Kernels J. Hertrich Christian Wald Fabian Altekrüger Paul Hagemann 53 27 0 19 May 2023
Energy-Based Sliced Wasserstein Distance Khai Nguyen Nhat Ho 56 22 0 26 Apr 2023
An Approximation Theory Framework for Measure-Transport Sampling Algorithms Ricardo Baptista Bamdad Hosseini Nikola B. Kovachki Youssef M. Marzouk A. Sagiv OT 80 17 0 27 Feb 2023
Diffusion Posterior Sampling for General Noisy Inverse Problems Hyungjin Chung Jeongsol Kim Michael T. McCann M. Klasky J. C. Ye DiffM 111 844 0 29 Sep 2022
PatchNR: Learning from Very Few Images by Patch Normalizing Flow Regularization Fabian Altekrüger Alexander Denker Paul Hagemann J. Hertrich Peter Maass Gabriele Steidl MedIm 50 26 0 24 May 2022
Revisiting Sliced Wasserstein on Images: From Vectorization to Convolution Khai Nguyen Nhat Ho 52 25 0 04 Apr 2022
Variational Wasserstein gradient flow JiaoJiao Fan Qinsheng Zhang Amirhossein Taghvaei Yongxin Chen 123 57 0 04 Dec 2021
Conditional Image Generation with Score-Based Diffusion Models Georgios Batzolis Jan Stanczuk Carola-Bibiane Schönlieb Christian Etmann DiffM 40 192 0 26 Nov 2021
Stochastic Normalizing Flows for Inverse Problems: a Markov Chains Viewpoint Paul Hagemann J. Hertrich Gabriele Steidl BDL 71 39 0 23 Sep 2021
Optimizing Functionals on the Space of Probabilities with Input Convex Neural Networks David Alvarez-Melis Yair Schiff Youssef Mroueh 77 57 0 01 Jun 2021
Diffusion Schrödinger Bridge with Applications to Score-Based Generative Modeling Valentin De Bortoli James Thornton J. Heng Arnaud Doucet DiffM OT 104 467 0 01 Jun 2021
Score-Based Generative Modeling through Stochastic Differential Equations Yang Song Jascha Narain Sohl-Dickstein Diederik P. Kingma Abhishek Kumar Stefano Ermon Ben Poole DiffM SyDa 335 6,480 0 26 Nov 2020
SRFlow: Learning the Super-Resolution Space with Normalizing Flow Andreas Lugmayr Martin Danelljan Luc Van Gool Radu Timofte SupR DRL 85 360 0 25 Jun 2020
Improved Techniques for Training Score-Based Generative Models Yang Song Stefano Ermon DiffM 237 1,151 0 16 Jun 2020
Generalized Sliced Wasserstein Distances Soheil Kolouri Kimia Nadjahi Umut Simsekli Roland Badeau Gustavo K. Rohde 50 300 0 01 Feb 2019
Analyzing Inverse Problems with Invertible Neural Networks Lynton Ardizzone Jakob Kruse Sebastian J. Wirkert D. Rahner E. Pellegrini R. Klessen Lena Maier-Hein Carsten Rother Ullrich Kothe 60 493 0 14 Aug 2018
Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms Han Xiao Kashif Rasul Roland Vollgraf 283 8,883 0 25 Aug 2017
Deep Learning Face Attributes in the Wild Ziwei Liu Ping Luo Xiaogang Wang Xiaoou Tang CVBM 244 8,408 0 28 Nov 2014
Auto-Encoding Variational Bayes Diederik P. Kingma Max Welling BDL 452 16,929 0 20 Dec 2013
Equivalence of distance-based and RKHS-based statistics in hypothesis testing Dino Sejdinovic Bharath K. Sriperumbudur Arthur Gretton Kenji Fukumizu 215 685 0 25 Jul 2012
Universality, Characteristic Kernels and RKHS Embedding of Measures Bharath K. Sriperumbudur Kenji Fukumizu Gert R. G. Lanckriet 224 530 0 03 Mar 2010
A Kernel Method for the Two-Sample Problem Arthur Gretton Karsten Borgwardt Malte J. Rasch Bernhard Schölkopf Alex Smola 231 2,360 0 15 May 2008