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Regularized Stein Variational Gradient Flow
v1v2 (latest)

Regularized Stein Variational Gradient Flow

15 November 2022
Ye He
Krishnakumar Balasubramanian
Bharath K. Sriperumbudur
Jianfeng Lu
    OT
ArXiv (abs)PDFHTML

Papers citing "Regularized Stein Variational Gradient Flow"

11 / 11 papers shown
Title
Hessian-guided Perturbed Wasserstein Gradient Flows for Escaping Saddle Points
Hessian-guided Perturbed Wasserstein Gradient Flows for Escaping Saddle Points
Naoya Yamamoto
Juno Kim
Taiji Suzuki
129
0
0
21 Sep 2025
Stationary MMD Points for Cubature
Stationary MMD Points for Cubature
Zonghao Chen
Toni Karvonen
Heishiro Kanagawa
F. Briol
Chris J. Oates
256
1
0
27 May 2025
Inclusive KL Minimization: A Wasserstein-Fisher-Rao Gradient Flow
  Perspective
Inclusive KL Minimization: A Wasserstein-Fisher-Rao Gradient Flow Perspective
Jia-Jie Zhu
420
3
0
31 Oct 2024
Kernel Approximation of Fisher-Rao Gradient Flows
Kernel Approximation of Fisher-Rao Gradient Flows
Jia Jie Zhu
Alexander Mielke
335
6
0
27 Oct 2024
Improved Finite-Particle Convergence Rates for Stein Variational Gradient Descent
Improved Finite-Particle Convergence Rates for Stein Variational Gradient DescentInternational Conference on Learning Representations (ICLR), 2024
Sayan Banerjee
Krishnakumar Balasubramanian
Promit Ghosal
275
7
0
13 Sep 2024
Wasserstein Gradient Boosting: A General Framework with Applications to
  Posterior Regression
Wasserstein Gradient Boosting: A General Framework with Applications to Posterior RegressionNeural Information Processing Systems (NeurIPS), 2024
Takuo Matsubara
153
4
0
15 May 2024
Zeroth-Order Sampling Methods for Non-Log-Concave Distributions:
  Alleviating Metastability by Denoising Diffusion
Zeroth-Order Sampling Methods for Non-Log-Concave Distributions: Alleviating Metastability by Denoising Diffusion
Ye He
Kevin Rojas
Molei Tao
DiffM
377
17
0
27 Feb 2024
Sampling via Gradient Flows in the Space of Probability Measures
Sampling via Gradient Flows in the Space of Probability Measures
Yifan Chen
Daniel Zhengyu Huang
Jiaoyang Huang
Sebastian Reich
Andrew M. Stuart
312
19
0
05 Oct 2023
Towards Understanding the Dynamics of Gaussian-Stein Variational
  Gradient Descent
Towards Understanding the Dynamics of Gaussian-Stein Variational Gradient DescentNeural Information Processing Systems (NeurIPS), 2023
Tianle Liu
Promit Ghosal
Krishnakumar Balasubramanian
Natesh S. Pillai
388
14
0
23 May 2023
Forward-backward Gaussian variational inference via JKO in the
  Bures-Wasserstein Space
Forward-backward Gaussian variational inference via JKO in the Bures-Wasserstein SpaceInternational Conference on Machine Learning (ICML), 2023
Michael Diao
Krishnakumar Balasubramanian
Sinho Chewi
Adil Salim
BDL
135
35
0
10 Apr 2023
Posterior sampling with CNN-based, Plug-and-Play regularization with
  applications to Post-Stack Seismic Inversion
Posterior sampling with CNN-based, Plug-and-Play regularization with applications to Post-Stack Seismic Inversion
M. Izzatullah
T. Alkhalifah
J. Romero
M. Corrales
N. Luiken
M. Ravasi
217
2
0
30 Dec 2022
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