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Scalable Importance Tempering and Bayesian Variable Selection

1 May 2018

Papers citing "Scalable Importance Tempering and Bayesian Variable Selection"

24 / 24 papers shown

Title
A geometric approach to informed MCMC sampling Vivekananda Roy 65 0 0 13 Jun 2024
Dimension-free Relaxation Times of Informed MCMC Samplers on Discrete Spaces Hyunwoong Chang Quan Zhou 77 6 0 05 Apr 2024
Control Variates for MCMC Leah South Matthew Sutton 38 0 0 12 Feb 2024
Adaptive MCMC for Bayesian variable selection in generalised linear models and survival models Xitong Liang Samuel Livingstone Jim Griffin 66 6 0 01 Aug 2023
Importance is Important: A Guide to Informed Importance Tempering Methods Guanxun Li Aaron Smith Quan Zhou 72 2 0 13 Apr 2023
Variable-Complexity Weighted-Tempered Gibbs Samplers for Bayesian Variable Selection Lan V. Truong 51 0 0 06 Apr 2023
Linear Complexity Gibbs Sampling for Generalized Labeled Multi-Bernoulli Filtering Changbeom Shim B. Vo B. Vo Jonah Ong Diluka Moratuwage 68 14 0 29 Nov 2022
Robust leave-one-out cross-validation for high-dimensional Bayesian models Luca Silva Giacomo Zanella 33 8 0 19 Sep 2022
Bayesian Variable Selection in a Million Dimensions M. Jankowiak BDL 49 3 0 02 Aug 2022
Computing Bayes: From Then 'Til Now' G. Martin David T. Frazier Christian P. Robert 93 16 0 01 Aug 2022
Rapidly Mixing Multiple-try Metropolis Algorithms for Model Selection Problems Hyunwoong Chang Changwoo J. Lee Z. Luo H. Sang Quan Zhou 54 11 0 01 Jul 2022
Adaptive random neighbourhood informed Markov chain Monte Carlo for high-dimensional Bayesian variable Selection Xitong Liang Samuel Livingstone Jim Griffin BDL 58 10 0 22 Oct 2021
Rapid Convergence of Informed Importance Tempering Quan Zhou Aaron Smith 53 10 0 22 Jul 2021
Fast Bayesian Variable Selection in Binomial and Negative Binomial Regression M. Jankowiak BDL 26 3 0 28 Jun 2021
Dimension-free Mixing for High-dimensional Bayesian Variable Selection Quan Zhou Jun Yang Dootika Vats Gareth O. Roberts Jeffrey S. Rosenthal 47 26 0 12 May 2021
A Metropolized adaptive subspace algorithm for high-dimensional Bayesian variable selection C. Staerk M. Kateri I. Ntzoufras 6 1 0 03 May 2021
Sticky PDMP samplers for sparse and local inference problems J. Bierkens Sebastiano Grazzi Frank van der Meulen Moritz Schauer 62 15 0 15 Mar 2021
Approximate Laplace approximations for scalable model selection D. Rossell Oriol Abril A. Bhattacharya 69 16 0 14 Dec 2020
Reversible Jump PDMP Samplers for Variable Selection Augustin Chevallier Paul Fearnhead Matthew Sutton 57 18 0 22 Oct 2020
Model Based Screening Embedded Bayesian Variable Selection for Ultra-high Dimensional Settings Dongjin Li Somak Dutta Vivekananda Roy 62 11 0 13 Jun 2020
Computing Bayes: Bayesian Computation from 1763 to the 21st Century G. Martin David T. Frazier Christian P. Robert 95 17 0 14 Apr 2020
Revisiting the balance heuristic for estimating normalising constants F. Medina-Aguayo R. Everitt 29 2 0 18 Aug 2019
Additive Bayesian variable selection under censoring and misspecification D. Rossell F. Rubio CML 46 20 0 31 Jul 2019
In Search of Lost (Mixing) Time: Adaptive Markov chain Monte Carlo schemes for Bayesian variable selection with very large p Jim Griffin Krys Latuszynski M. Steel AI4TS 77 35 0 18 Aug 2017