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A Framework for Adaptive MCMC Targeting Multimodal Distributions

6 December 2018

E. Pompe

Chris Holmes

K. Latuszyñski

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Papers citing "A Framework for Adaptive MCMC Targeting Multimodal Distributions"

40 / 40 papers shown

Title
Branching Stein Variational Gradient Descent for sampling multimodal distributions Isaias Banales Arturo Jaramillo Heli Ricalde Guerrero 17 0 0 16 Jun 2025
Upper and lower bounds on the subgeometric convergence of adaptive Markov chain Monte Carlo Austin Brown Jeffrey S. Rosenthal 103 0 0 26 Nov 2024
On theoretical guarantees and a blessing of dimensionality for nonconvex sampling Martin Chak 101 2 0 12 Nov 2024
On MCMC mixing under unidentified nonparametric models with an application to survival predictions under transformation models Chong Zhong Jin Yang Junshan Shen Catherine C. Liu Zhaohai Li 78 0 0 03 Nov 2024
Learned Reference-based Diffusion Sampling for multi-modal distributions Maxence Noble Louis Grenioux Marylou Gabrié Alain Durmus DiffM 121 6 0 25 Oct 2024
Training Neural Samplers with Reverse Diffusive KL Divergence Wenlin Chen Jiajun He Mingtian Zhang David Barber José Miguel Hernández-Lobato DiffM 126 8 0 16 Oct 2024
An invitation to adaptive Markov chain Monte Carlo convergence theory Pietari Laitinen M. Vihola 61 1 0 27 Aug 2024
Adaptive Stereographic MCMC Cameron Bell Krzystof Łatuszyński Gareth O. Roberts 65 1 0 21 Aug 2024
Symmetry-driven embedding of networks in hyperbolic space Simon Lizotte Jean-Gabriel Young Antoine Allard 74 1 0 15 Jun 2024
Weak convergence of adaptive Markov chain Monte Carlo Austin Brown Jeffrey S. Rosenthal 27 1 0 02 Jun 2024
Repelling-Attracting Hamiltonian Monte Carlo Siddharth Vishwanath Hyungsuk Tak 40 0 0 07 Mar 2024
On a Neural Implementation of Brenier's Polar Factorization Nina Vesseron Marco Cuturi 116 2 0 05 Mar 2024
Almost sure convergence rates of adaptive increasingly rare Markov chain Monte Carlo Julian Hofstadler Krzysztof Latuszynski Gareth O. Roberts Daniel Rudolf 30 4 0 19 Feb 2024
Diffusive Gibbs Sampling Jiajun He Mingtian Zhang Brooks Paige José Miguel Hernández-Lobato David Barber 143 11 0 05 Feb 2024
Graph-accelerated Markov Chain Monte Carlo using Approximate Samples Leo L. Duan Anirban Bhattacharya 91 1 0 25 Jan 2024
Channelling Multimodality Through a Unimodalizing Transport: Warp-U Sampler and Stochastic Bridge Sampling Fei Ding David E. Jones Shiyuan He Xiao-Li Meng OT 46 0 0 01 Jan 2024
A Theory of Non-Acyclic Generative Flow Networks Leo Maxime Brunswic Yinchuan Li Yushun Xu Shangling Jui Lizhuang Ma 100 6 0 23 Dec 2023
Using Perturbation to Improve Goodness-of-Fit Tests based on Kernelized Stein Discrepancy Xingtu Liu Andrew B. Duncan Axel Gandy 76 7 0 28 Apr 2023
Machine Learning and the Future of Bayesian Computation Steven Winter Trevor Campbell Lizhen Lin Sanvesh Srivastava David B. Dunson TPM 77 4 0 21 Apr 2023
Diverse Policy Optimization for Structured Action Space Wenhao Li Baoxiang Wang Shanchao Yang H. Zha OffRL 70 1 0 23 Feb 2023
Kernel Stein Discrepancy thinning: a theoretical perspective of pathologies and a practical fix with regularization Clément Bénard B. Staber Sébastien Da Veiga 82 5 0 31 Jan 2023
Sampling using Adaptive Regenerative Processes Hector McKimm Andi Q. Wang M. Pollock Christian P. Robert Gareth O. Roberts 69 1 0 18 Oct 2022
Approximate Methods for Bayesian Computation Radu V. Craiu Evgeny Levi 41 5 0 06 Oct 2022
Cyclical Kernel Adaptive Metropolis J. Li Yimeng Zeng Wen-Ping Guo 25 0 0 29 Jun 2022
Stereographic Markov Chain Monte Carlo Jun Yang K. Latuszyñski Gareth O. Roberts 82 14 0 24 May 2022
Annealed Leap-Point Sampler for Multimodal Target Distributions Nicholas G. Tawn M. Moores Gareth O. Roberts 68 6 0 24 Dec 2021
The Apogee to Apogee Path Sampler Chris Sherlock S. Urbas Matthew Ludkin 82 6 0 15 Dec 2021
GFlowNet Foundations Yoshua Bengio Salem Lahlou T. Deleu J. E. Hu Mo Tiwari Emmanuel Bengio 98 240 0 17 Nov 2021
Sampling from multimodal distributions using tempered Hamiltonian transitions Joonha Park 24 2 0 12 Nov 2021
The Ball Pit Algorithm: A Markov Chain Monte Carlo Method Based on Path Integrals Miguel Fudolig Réka Howard 27 0 0 05 Nov 2021
Local-Global MCMC kernels: the best of both worlds S. Samsonov E. Lagutin Marylou Gabrié Alain Durmus A. Naumov Eric Moulines 59 15 0 04 Nov 2021
Adaptation of the Independent Metropolis-Hastings Sampler with Normalizing Flow Proposals James A. Brofos Marylou Gabrié Marcus A. Brubaker Roy R. Lederman 50 9 0 25 Oct 2021
Adaptive random neighbourhood informed Markov chain Monte Carlo for high-dimensional Bayesian variable Selection Xitong Liang Samuel Livingstone Jim Griffin BDL 70 10 0 22 Oct 2021
Nested Sampling for Non-Gaussian Inference in SLAM Factor Graphs Qiangqiang Huang Alan Papalia J. Leonard 72 4 0 22 Sep 2021
LSB: Local Self-Balancing MCMC in Discrete Spaces Emanuele Sansone 48 10 0 08 Sep 2021
Cauchy Markov Random Field Priors for Bayesian Inversion Neil K. Chada L. Roininen Jarkko Suuronen 48 24 0 26 May 2021
Sampling by Divergence Minimization Ameer Dharamshi V. Ngo Jeffrey S. Rosenthal 66 4 0 02 May 2021
Adaptive schemes for piecewise deterministic Monte Carlo algorithms Andrea Bertazzi J. Bierkens 43 10 0 27 Dec 2020
A Metropolis-class sampler for targets with non-convex support John Moriarty Jure Vogrinc Alessandro Zocca 60 5 0 23 May 2019
Scalable Nonparametric Sampling from Multimodal Posteriors with the Posterior Bootstrap Edwin Fong Simon Lyddon Chris Holmes 174 36 0 08 Feb 2019