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Wasserstein Gradient Flows for Moreau Envelopes of f-Divergences in Reproducing Kernel Hilbert Spaces

Wasserstein Gradient Flows for Moreau Envelopes of f-Divergences in Reproducing Kernel Hilbert Spaces

7 February 2024
Viktor Stein
Sebastian Neumayer
Gabriele Steidl
Nicolaj Rux
ArXivPDFHTML

Papers citing "Wasserstein Gradient Flows for Moreau Envelopes of f-Divergences in Reproducing Kernel Hilbert Spaces"

22 / 22 papers shown
Title
Ultra-fast feature learning for the training of two-layer neural networks in the two-timescale regime
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
68
0
0
25 Apr 2025
Smoothed Distance Kernels for MMDs and Applications in Wasserstein Gradient Flows
Smoothed Distance Kernels for MMDs and Applications in Wasserstein Gradient Flows
Nicolaj Rux
Michael Quellmalz
Gabriele Steidl
54
0
0
10 Apr 2025
DDEQs: Distributional Deep Equilibrium Models through Wasserstein Gradient Flows
DDEQs: Distributional Deep Equilibrium Models through Wasserstein Gradient Flows
Jonathan Geuter
Clément Bonet
Anna Korba
David Alvarez-Melis
123
0
0
03 Mar 2025
Inclusive KL Minimization: A Wasserstein-Fisher-Rao Gradient Flow
  Perspective
Inclusive KL Minimization: A Wasserstein-Fisher-Rao Gradient Flow Perspective
Jia-Jie Zhu
132
1
0
31 Oct 2024
Forward-Euler time-discretization for Wasserstein gradient flows can be
  wrong
Forward-Euler time-discretization for Wasserstein gradient flows can be wrong
Yewei Xu
Qin Li
50
1
0
12 Jun 2024
Interaction-Force Transport Gradient Flows
Interaction-Force Transport Gradient Flows
E. Gladin
Pavel Dvurechensky
Alexander Mielke
Jia Jie Zhu
OT
54
6
0
27 May 2024
Generative Sliced MMD Flows with Riesz Kernels
Generative Sliced MMD Flows with Riesz Kernels
J. Hertrich
Christian Wald
Fabian Altekrüger
Paul Hagemann
46
27
0
19 May 2023
Estimation Beyond Data Reweighting: Kernel Method of Moments
Estimation Beyond Data Reweighting: Kernel Method of Moments
Heiner Kremer
Yassine Nemmour
Bernhard Schölkopf
Jia-Jie Zhu
59
7
0
18 May 2023
MixFlows: principled variational inference via mixed flows
MixFlows: principled variational inference via mixed flows
Zuheng Xu
Na Chen
Trevor Campbell
95
9
0
16 May 2022
KALE Flow: A Relaxed KL Gradient Flow for Probabilities with Disjoint
  Support
KALE Flow: A Relaxed KL Gradient Flow for Probabilities with Disjoint Support
Pierre Glaser
Michael Arbel
Arthur Gretton
87
40
0
16 Jun 2021
Moreau-Yosida $f$-divergences
Moreau-Yosida fff-divergences
Dávid Terjék
23
5
0
26 Feb 2021
Invertible Neural Networks versus MCMC for Posterior Reconstruction in
  Grazing Incidence X-Ray Fluorescence
Invertible Neural Networks versus MCMC for Posterior Reconstruction in Grazing Incidence X-Ray Fluorescence
A. Andrle
N. Farchmin
Paul Hagemann
Sebastian Heidenreich
V. Soltwisch
Gabriele Steidl
89
16
0
05 Feb 2021
Optimal Bounds between $f$-Divergences and Integral Probability Metrics
Optimal Bounds between fff-Divergences and Integral Probability Metrics
R. Agrawal
Thibaut Horel
31
38
0
10 Jun 2020
Generalized Energy Based Models
Generalized Energy Based Models
Michael Arbel
Liang Zhou
Arthur Gretton
DRL
87
80
0
10 Mar 2020
Smoothness and Stability in GANs
Smoothness and Stability in GANs
Casey Chu
Kentaro Minami
Kenji Fukumizu
GAN
45
56
0
11 Feb 2020
PyTorch: An Imperative Style, High-Performance Deep Learning Library
PyTorch: An Imperative Style, High-Performance Deep Learning Library
Adam Paszke
Sam Gross
Francisco Massa
Adam Lerer
James Bradbury
...
Sasank Chilamkurthy
Benoit Steiner
Lu Fang
Junjie Bai
Soumith Chintala
ODL
384
42,299
0
03 Dec 2019
Sinkhorn Divergences for Unbalanced Optimal Transport
Sinkhorn Divergences for Unbalanced Optimal Transport
Thibault Séjourné
Jean Feydy
Franccois-Xavier Vialard
A. Trouvé
Gabriel Peyré
OT
68
74
0
28 Oct 2019
Strictly proper kernel scores and characteristic kernels on compact
  spaces
Strictly proper kernel scores and characteristic kernels on compact spaces
Ingo Steinwart
J. Ziegel
43
24
0
14 Dec 2017
Uncertain programming model for multi-item solid transportation problem
Uncertain programming model for multi-item solid transportation problem
Hasan Dalman
94
735
0
31 May 2016
Kernel Distribution Embeddings: Universal Kernels, Characteristic
  Kernels and Kernel Metrics on Distributions
Kernel Distribution Embeddings: Universal Kernels, Characteristic Kernels and Kernel Metrics on Distributions
Carl-Johann Simon-Gabriel
Bernhard Schölkopf
37
92
0
18 Apr 2016
Variational Inference: A Review for Statisticians
Variational Inference: A Review for Statisticians
David M. Blei
A. Kucukelbir
Jon D. McAuliffe
BDL
244
4,778
0
04 Jan 2016
Universality, Characteristic Kernels and RKHS Embedding of Measures
Universality, Characteristic Kernels and RKHS Embedding of Measures
Bharath K. Sriperumbudur
Kenji Fukumizu
Gert R. G. Lanckriet
201
528
0
03 Mar 2010
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