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Accelerating Langevin Sampling with Birth-death

Accelerating Langevin Sampling with Birth-death

23 May 2019
Yulong Lu
Jianfeng Lu
J. Nolen
ArXivPDFHTML

Papers citing "Accelerating Langevin Sampling with Birth-death"

14 / 14 papers shown
Title
New affine invariant ensemble samplers and their dimensional scaling
New affine invariant ensemble samplers and their dimensional scaling
Yifan Chen
19
0
0
05 May 2025
Computational and Statistical Asymptotic Analysis of the JKO Scheme for Iterative Algorithms to update distributions
Computational and Statistical Asymptotic Analysis of the JKO Scheme for Iterative Algorithms to update distributions
Shang Wu
Yazhen Wang
43
0
0
11 Jan 2025
GAD-PVI: A General Accelerated Dynamic-Weight Particle-Based Variational
  Inference Framework
GAD-PVI: A General Accelerated Dynamic-Weight Particle-Based Variational Inference Framework
Fangyikang Wang
Huminhao Zhu
Chao Zhang
Han Zhao
Hui Qian
24
5
0
27 Dec 2023
Algorithms for mean-field variational inference via polyhedral optimization in the Wasserstein space
Algorithms for mean-field variational inference via polyhedral optimization in the Wasserstein space
Yiheng Jiang
Sinho Chewi
Aram-Alexandre Pooladian
29
7
0
05 Dec 2023
Multi-Objective Optimization via Wasserstein-Fisher-Rao Gradient Flow
Multi-Objective Optimization via Wasserstein-Fisher-Rao Gradient Flow
Yinuo Ren
Tesi Xiao
Tanmay Gangwani
A. Rangi
Holakou Rahmanian
Lexing Ying
Subhajit Sanyal
25
2
0
22 Nov 2023
A Computational Framework for Solving Wasserstein Lagrangian Flows
A Computational Framework for Solving Wasserstein Lagrangian Flows
Kirill Neklyudov
Rob Brekelmans
Alexander Tong
Lazar Atanackovic
Qiang Liu
Alireza Makhzani
OT
31
17
0
16 Oct 2023
Accelerating optimization over the space of probability measures
Accelerating optimization over the space of probability measures
Shi Chen
Wenxuan Wu
Yuhang Yao
Stephen J. Wright
26
4
0
06 Oct 2023
GenPhys: From Physical Processes to Generative Models
GenPhys: From Physical Processes to Generative Models
Ziming Liu
Di Luo
Yilun Xu
Tommi Jaakkola
M. Tegmark
AI4CE
14
14
0
05 Apr 2023
From Optimization to Sampling Through Gradient Flows
From Optimization to Sampling Through Gradient Flows
Nicolas García Trillos
B. Hosseini
D. Sanz-Alonso
15
11
0
22 Feb 2023
Learning Gaussian Mixtures Using the Wasserstein-Fisher-Rao Gradient
  Flow
Learning Gaussian Mixtures Using the Wasserstein-Fisher-Rao Gradient Flow
Yuling Yan
Kaizheng Wang
Philippe Rigollet
44
20
0
04 Jan 2023
Efficient Gradient Flows in Sliced-Wasserstein Space
Efficient Gradient Flows in Sliced-Wasserstein Space
Clément Bonet
Nicolas Courty
Franccois Septier
Lucas Drumetz
29
21
0
21 Oct 2021
Information Newton's flow: second-order optimization method in
  probability space
Information Newton's flow: second-order optimization method in probability space
Yifei Wang
Wuchen Li
12
31
0
13 Jan 2020
The Zig-Zag Process and Super-Efficient Sampling for Bayesian Analysis
  of Big Data
The Zig-Zag Process and Super-Efficient Sampling for Bayesian Analysis of Big Data
J. Bierkens
Paul Fearnhead
Gareth O. Roberts
58
231
0
11 Jul 2016
MCMC using Hamiltonian dynamics
MCMC using Hamiltonian dynamics
Radford M. Neal
185
3,262
0
09 Jun 2012
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