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The Metropolis-Hastings algorithm
v1v2v3 (latest)

The Metropolis-Hastings algorithm

8 April 2015
Christian P. Robert
ArXiv (abs)PDFHTML

Papers citing "The Metropolis-Hastings algorithm"

36 / 36 papers shown
Inference-time Stochastic Refinement of GRU-Normalizing Flow for Real-time Video Motion Transfer
Inference-time Stochastic Refinement of GRU-Normalizing Flow for Real-time Video Motion Transfer
Tasmiah Haque
Srinjoy Das
AI4TS
141
0
0
03 Dec 2025
A machine learning approach to automation and uncertainty evaluation for self-validating thermocouples
A machine learning approach to automation and uncertainty evaluation for self-validating thermocouplesAIP Conference Proceedings (AIP Conf. Proc.), 2025
Samuel Bilson
Andrew Thompson
Declan Tucker
Jonathan Pearce
88
7
0
21 Oct 2025
An Introduction to Zero-Order Optimization Techniques for Robotics
An Introduction to Zero-Order Optimization Techniques for Robotics
Armand Jordana
J. Zhang
Joseph Amigo
Ludovic Righetti
219
7
0
27 Jun 2025
Textual Bayes: Quantifying Uncertainty in LLM-Based Systems
Textual Bayes: Quantifying Uncertainty in LLM-Based Systems
Brendan Leigh Ross
Noël Vouitsis
Atiyeh Ashari Ghomi
Rasa Hosseinzadeh
Ji Xin
...
Yi Sui
Shiyi Hou
Kin Kwan Leung
Gabriel Loaiza-Ganem
Jesse C. Cresswell
484
3
0
11 Jun 2025
An AI-powered Bayesian generative modeling approach for causal inference in observational studies
An AI-powered Bayesian generative modeling approach for causal inference in observational studies
Qiao Liu
W. Wong
CML
361
2
0
01 Jan 2025
Social Distancing Induced Coronavirus Optimization Algorithm (COVO):
  Application to Multimodal Function Optimization and Noise Removal
Social Distancing Induced Coronavirus Optimization Algorithm (COVO): Application to Multimodal Function Optimization and Noise Removal
Om Ramakisan Varma
Mala Kalra
153
0
0
26 Nov 2024
Exactly Minimax-Optimal Locally Differentially Private Sampling
Exactly Minimax-Optimal Locally Differentially Private SamplingNeural Information Processing Systems (NeurIPS), 2024
Hyun-Young Park
Shahab Asoodeh
Si-Hyeon Lee
421
5
0
30 Oct 2024
Estimating the Probabilities of Rare Outputs in Language Models
Estimating the Probabilities of Rare Outputs in Language ModelsInternational Conference on Learning Representations (ICLR), 2024
Gabriel Wu
Jacob Hilton
AAMLUQCV
432
6
0
17 Oct 2024
Incorporating additional evidence as prior information to resolve
  non-identifiability in Bayesian disease model calibration
Incorporating additional evidence as prior information to resolve non-identifiability in Bayesian disease model calibration
Daria Semochkina
Cathal Walsh
80
5
0
18 Jul 2024
Fast Gibbs sampling for the local and global trend Bayesian exponential
  smoothing model
Fast Gibbs sampling for the local and global trend Bayesian exponential smoothing model
Xueying Long
Daniel F. Schmidt
Christoph Bergmeir
Slawek Smyl
152
0
0
29 Jun 2024
Fairness in Social Influence Maximization via Optimal Transport
Fairness in Social Influence Maximization via Optimal Transport
Shubham Chowdhary
Giulia De Pasquale
Nicolas Lanzetti
Ana-Andreea Stoica
Florian Dorfler
147
4
0
25 Jun 2024
BlackJAX: Composable Bayesian inference in JAX
BlackJAX: Composable Bayesian inference in JAX
Alberto Cabezas
Adrien Corenflos
Junpeng Lao
Rémi Louf
Antoine Carnec
...
Kevin P. Murphy
Juan Camilo Orduz
Karm Patel
Xi Wang
Robert Zinkov
DRLMLAU
259
71
0
16 Feb 2024
Towards Chip-in-the-loop Spiking Neural Network Training via
  Metropolis-Hastings Sampling
Towards Chip-in-the-loop Spiking Neural Network Training via Metropolis-Hastings Sampling
Ali Safa
Vikrant Jaltare
Samira Sebt
Kameron Gano
Johannes Leugering
Georges G. E. Gielen
Gert Cauwenberghs
216
2
0
09 Feb 2024
Sampling in Unit Time with Kernel Fisher-Rao Flow
Sampling in Unit Time with Kernel Fisher-Rao FlowInternational Conference on Machine Learning (ICML), 2024
A. Maurais
Youssef Marzouk
378
28
0
08 Jan 2024
PaperToPlace: Transforming Instruction Documents into Spatialized and
  Context-Aware Mixed Reality Experiences
PaperToPlace: Transforming Instruction Documents into Spatialized and Context-Aware Mixed Reality ExperiencesACM Symposium on User Interface Software and Technology (UIST), 2023
Chong Chen
Cuong Nguyen
Jane Hoffswell
Jennifer Healey
Trung Bui
Nadir Weibel
145
18
0
26 Aug 2023
Bayesian Synthetic Likelihood
Bayesian Synthetic Likelihood
David T. Frazier
Christopher C. Drovandi
David J. Nott
496
244
0
09 May 2023
Bayesian neural networks via MCMC: a Python-based tutorial
Bayesian neural networks via MCMC: a Python-based tutorialIEEE Access (IEEE Access), 2023
Rohitash Chandra
Royce Chen
Joshua Simmons
BDL
381
27
0
02 Apr 2023
Inference in Marginal Structural Models by Automatic Targeted Bayesian
  and Minimum Loss-Based Estimation
Inference in Marginal Structural Models by Automatic Targeted Bayesian and Minimum Loss-Based Estimation
Herbert Susmann
Antoine Chambaz
CML
122
1
0
25 Jan 2023
Computing Bayes: From Then 'Til Now'
Computing Bayes: From Then 'Til Now'Statistical Science (Statist. Sci.), 2022
G. Martin
David T. Frazier
Christian P. Robert
371
18
0
01 Aug 2022
Variational Inference for Nonlinear Inverse Problems via Neural Net
  Kernels: Comparison to Bayesian Neural Networks, Application to Topology
  Optimization
Variational Inference for Nonlinear Inverse Problems via Neural Net Kernels: Comparison to Bayesian Neural Networks, Application to Topology OptimizationComputer Methods in Applied Mechanics and Engineering (CMAME), 2022
Vahid Keshavarzzadeh
Robert M. Kirby
A. Narayan
BDL
223
3
0
07 May 2022
DeepBayes -- an estimator for parameter estimation in stochastic
  nonlinear dynamical models
DeepBayes -- an estimator for parameter estimation in stochastic nonlinear dynamical models
Anubhab Ghosh
M. Abdalmoaty
Saikat Chatterjee
H. Hjalmarsson
BDL
202
6
0
04 May 2022
A Framework for Controlling Multi-Robot Systems Using Bayesian
  Optimization and Linear Combination of Vectors
A Framework for Controlling Multi-Robot Systems Using Bayesian Optimization and Linear Combination of Vectors
Stephen Jacobs
R. Butts
Yue Gu
Ali Baheri
G. Pereira
148
2
0
23 Mar 2022
Bayesian Nonlinear Models for Repeated Measurement Data: An Overview,
  Implementation, and Applications
Bayesian Nonlinear Models for Repeated Measurement Data: An Overview, Implementation, and Applications
Se Yoon Lee
473
23
0
28 Jan 2022
Efficient Learning of the Parameters of Non-Linear Models using
  Differentiable Resampling in Particle Filters
Efficient Learning of the Parameters of Non-Linear Models using Differentiable Resampling in Particle FiltersIEEE Transactions on Signal Processing (IEEE TSP), 2021
Conor Rosato
Vincent Beraud
P. Horridge
Thomas B. Schon
Simon Maskell
369
24
0
02 Nov 2021
Gaussian Processes to speed up MCMC with automatic
  exploratory-exploitation effect
Gaussian Processes to speed up MCMC with automatic exploratory-exploitation effect
A. Benavoli
J. Wyse
Arthur J. White
GP
127
0
0
28 Sep 2021
Schr{ö}dinger-F{ö}llmer Sampler: Sampling without Ergodicity
Schr{ö}dinger-F{ö}llmer Sampler: Sampling without ErgodicityIEEE Transactions on Information Theory (IEEE Trans. Inf. Theory), 2021
Jian Huang
Yuling Jiao
Lican Kang
Xu Liao
Jin Liu
Yanyan Liu
313
26
0
21 Jun 2021
Discrepancies in Epidemiological Modeling of Aggregated Heterogeneous
  Data
Discrepancies in Epidemiological Modeling of Aggregated Heterogeneous Data
Anna L. Trella
Peniel Argaw
Michelle M. Li
J. Hay
77
1
0
20 Jun 2021
Large-Scale Wasserstein Gradient Flows
Large-Scale Wasserstein Gradient FlowsNeural Information Processing Systems (NeurIPS), 2021
Petr Mokrov
Alexander Korotin
Lingxiao Li
Aude Genevay
Justin Solomon
Evgeny Burnaev
371
96
0
01 Jun 2021
Advances in Importance Sampling
Advances in Importance Sampling
Victor Elvira
Luca Martino
AI4TS
359
123
0
10 Feb 2021
CNN with large memory layers
CNN with large memory layers
R. Karimov
Yury Malkov
Karim Iskakov
Victor Lempitsky
289
0
0
27 Jan 2021
Stabilizing Invertible Neural Networks Using Mixture Models
Stabilizing Invertible Neural Networks Using Mixture ModelsInverse Problems (IP), 2020
Paul Hagemann
Sebastian Neumayer
343
40
0
07 Sep 2020
Anytime Parallel Tempering
Anytime Parallel Tempering
Alix Marie d’Avigneau
Sumeetpal S. Singh
Lawrence M. Murray
LRM
312
1
0
26 Jun 2020
TensorFlow Quantum: A Software Framework for Quantum Machine Learning
TensorFlow Quantum: A Software Framework for Quantum Machine Learning
Michael Broughton
Guillaume Verdon
Trevor McCourt
Antonio J. Martinez
Jae Hyeon Yoo
...
Sergio Boixo
Dave Bacon
Alan K. Ho
Hartmut Neven
Masoud Mohseni
VLMAI4CE
245
220
0
06 Mar 2020
TATi-Thermodynamic Analytics ToolkIt: TensorFlow-based software for
  posterior sampling in machine learning applications
TATi-Thermodynamic Analytics ToolkIt: TensorFlow-based software for posterior sampling in machine learning applications
Frederik Heber
Zofia Trstanova
Benedict Leimkuhler
244
0
0
20 Mar 2019
Metropolis Sampling
Metropolis Sampling
Luca Martino
Victor Elvira
215
26
0
15 Apr 2017
MCMC Louvain for Online Community Detection
MCMC Louvain for Online Community Detection
Yves Darmaillac
S. Loustau
241
5
0
05 Dec 2016
1
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