Deep MMD Gradient Flow without adversarial training

Deep MMD Gradient Flow without adversarial training

10 May 2024

Alexandre Galashov

Valentin De Bortoli

Arthur Gretton

Papers citing "Deep MMD Gradient Flow without adversarial training"

8 / 8 papers shown

Title
Inclusive KL Minimization: A Wasserstein-Fisher-Rao Gradient Flow Perspective Jia-Jie Zhu 64 1 0 31 Oct 2024
Fast Summation of Radial Kernels via QMC Slicing Johannes Hertrich Tim Jahn Michael Quellmalz 16 5 0 02 Oct 2024
Fast Kernel Summation in High Dimensions via Slicing and Fourier Transforms Johannes Hertrich 16 7 0 16 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 11 2 0 13 Dec 2023
Adversarial Diffusion Distillation Axel Sauer Dominik Lorenz A. Blattmann Robin Rombach 138 326 0 28 Nov 2023
UFOGen: You Forward Once Large Scale Text-to-Image Generation via Diffusion GANs Yanwu Xu Yang Zhao Zhisheng Xiao Tingbo Hou 129 105 0 14 Nov 2023
Sampling is as easy as learning the score: theory for diffusion models with minimal data assumptions Sitan Chen Sinho Chewi Jungshian Li Yuanzhi Li Adil Salim Anru R. Zhang DiffM 123 245 0 22 Sep 2022
U-Net: Convolutional Networks for Biomedical Image Segmentation Olaf Ronneberger Philipp Fischer Thomas Brox SSeg 3DV 229 74,467 0 18 May 2015