KALE Flow: A Relaxed KL Gradient Flow for Probabilities with Disjoint Support

16 June 2021

Papers citing "KALE Flow: A Relaxed KL Gradient Flow for Probabilities with Disjoint Support"

7 / 7 papers shown

Title
Ultra-fast feature learning for the training of two-layer neural networks in the two-timescale regime Raphael Barboni Gabriel Peyré François-Xavier Vialard MLT 34 0 0 25 Apr 2025
DDEQs: Distributional Deep Equilibrium Models through Wasserstein Gradient Flows Jonathan Geuter Clément Bonet Anna Korba David Alvarez-Melis 61 0 0 03 Mar 2025
Deep MMD Gradient Flow without adversarial training Alexandre Galashov Valentin De Bortoli Arthur Gretton DiffM 40 7 0 10 May 2024
Wasserstein Gradient Flows for Moreau Envelopes of f-Divergences in Reproducing Kernel Hilbert Spaces Viktor Stein Sebastian Neumayer Gabriele Steidl Nicolaj Rux 50 9 0 07 Feb 2024
Data Interpolants -- That's What Discriminators in Higher-order Gradient-regularized GANs Are Siddarth Asokan C. Seelamantula 24 4 0 01 Jun 2023
Efficient Gradient Flows in Sliced-Wasserstein Space Clément Bonet Nicolas Courty Franccois Septier Lucas Drumetz 31 21 0 21 Oct 2021
Optimizing Functionals on the Space of Probabilities with Input Convex Neural Networks David Alvarez-Melis Yair Schiff Youssef Mroueh 40 52 0 01 Jun 2021