Communities
Connect sessions
AI calendar
Organizations
Join Slack
Contact Sales
Search
Open menu
Home
Papers
2106.03076
Cited By
v1
v2 (latest)
A Convergence Theory for SVGD in the Population Limit under Talagrand's Inequality T1
International Conference on Machine Learning (ICML), 2021
6 June 2021
Adil Salim
Lukang Sun
Peter Richtárik
Re-assign community
ArXiv (abs)
PDF
HTML
Github
Papers citing
"A Convergence Theory for SVGD in the Population Limit under Talagrand's Inequality T1"
18 / 18 papers shown
Gradient Flow Sampler-based Distributionally Robust Optimization
Zusen Xu
Jia Jie Zhu
161
0
0
29 Oct 2025
Adaptive Kernel Selection for Stein Variational Gradient Descent
Moritz Melcher
Simon Weissmann
Ashia C. Wilson
Jakob Zech
270
0
0
02 Oct 2025
Improved Finite-Particle Convergence Rates for Stein Variational Gradient Descent
International Conference on Learning Representations (ICLR), 2024
Sayan Banerjee
Krishnakumar Balasubramanian
Promit Ghosal
388
9
0
13 Sep 2024
Stein Variational Ergodic Search
Darrick Lee
Cameron J. Lerch
Fabio Ramos
Ian Abraham
353
9
0
17 Jun 2024
Long-time asymptotics of noisy SVGD outside the population limit
Victor Priser
Pascal Bianchi
Adil Salim
243
2
0
17 Jun 2024
Zeroth-Order Sampling Methods for Non-Log-Concave Distributions: Alleviating Metastability by Denoising Diffusion
Ye He
Kevin Rojas
Molei Tao
DiffM
522
22
0
27 Feb 2024
Bayesian Multi-Task Transfer Learning for Soft Prompt Tuning
Haeju Lee
Minchan Jeong
SeYoung Yun
Kee-Eung Kim
AAML
VPVLM
292
5
0
13 Feb 2024
Towards a Better Theoretical Understanding of Independent Subnetwork Training
International Conference on Machine Learning (ICML), 2023
Egor Shulgin
Peter Richtárik
AI4CE
412
8
0
28 Jun 2023
Provably Fast Finite Particle Variants of SVGD via Virtual Particle Stochastic Approximation
Neural Information Processing Systems (NeurIPS), 2023
Aniket Das
Dheeraj M. Nagaraj
494
8
0
27 May 2023
Learning Rate Free Sampling in Constrained Domains
Louis Sharrock
Lester W. Mackey
Christopher Nemeth
434
4
0
24 May 2023
Tuning-Free Maximum Likelihood Training of Latent Variable Models via Coin Betting
International Conference on Artificial Intelligence and Statistics (AISTATS), 2023
Louis Sharrock
Daniel Dodd
Christopher Nemeth
314
11
0
24 May 2023
Towards Understanding the Dynamics of Gaussian-Stein Variational Gradient Descent
Neural Information Processing Systems (NeurIPS), 2023
Tianle Liu
Promit Ghosal
Krishnakumar Balasubramanian
Natesh S. Pillai
564
16
0
23 May 2023
Augmented Message Passing Stein Variational Gradient Descent
Jiankui Zhou
Yue Qiu
211
0
0
18 May 2023
Forward-backward Gaussian variational inference via JKO in the Bures-Wasserstein Space
International Conference on Machine Learning (ICML), 2023
Michael Diao
Krishnakumar Balasubramanian
Sinho Chewi
Adil Salim
BDL
184
47
0
10 Apr 2023
Coin Sampling: Gradient-Based Bayesian Inference without Learning Rates
International Conference on Machine Learning (ICML), 2023
Louis Sharrock
Christopher Nemeth
BDL
457
10
0
26 Jan 2023
A Finite-Particle Convergence Rate for Stein Variational Gradient Descent
Neural Information Processing Systems (NeurIPS), 2022
Jiaxin Shi
Lester W. Mackey
380
31
0
17 Nov 2022
Regularized Stein Variational Gradient Flow
Ye He
Krishnakumar Balasubramanian
Bharath K. Sriperumbudur
Jianfeng Lu
OT
259
14
0
15 Nov 2022
Sampling with Mollified Interaction Energy Descent
International Conference on Learning Representations (ICLR), 2022
Lingxiao Li
Qiang Liu
Anna Korba
Mikhail Yurochkin
Justin Solomon
317
21
0
24 Oct 2022
1
Page 1 of 1
