Coin Sampling: Gradient-Based Bayesian Inference without Learning Rates

International Conference on Machine Learning (ICML)

July 2023 · Louis Sharrock, Christopher Nemeth

Preferential Subsampling for Stochastic Gradient Langevin Dynamics

International Conference on Artificial Intelligence and Statistics (AISTATS)

April 2023 · Srshti Putcha, Christopher Nemeth, Paul Fearnhead

Transport Elliptical Slice Sampling

International Conference on Artificial Intelligence and Statistics (AISTATS)

April 2023 · Alberto Cabezas, Christopher Nemeth

Multivariate sensitivity analysis for a large-scale climate impact and adaptation model

Journal of the Royal Statistical Society: Series C

April 2023 · Oluwole Oyebamiji, Christopher Nemeth, Paula A Harrison, Robert W Dunford, George Cojocaru

Efficient and generalizable tuning strategies for stochastic gradient MCMC

Statistics and Computing

April 2023 · Jeremie Coullon, Leah South, Christopher Nemeth

Sequential Estimation of Temporally Evolving Latent Space Network Models

Computational Statistics and Data Analysis

March 2023 · Kathryn Turnbull, Christopher Nemeth, Matthew Nunes, Tyler McCormick

Distances for Comparing Multisets and Sequences

arXiv preprint

June 2022 · George Bolt, Simon Lunagomez, Christopher Nemeth

Semi-exact control functionals from Sard’s method

Biometrika

June 2022 · Leah F South, Toni Karvonen, Christopher Nemeth, Mark Girolami, Chris J Oates

GaussianProcesses.jl: A Nonparametric Bayes Package for the Julia Language

Journal of Statistical Software

April 2022 · Jamie Fairbrother, Christopher Nemeth, Maxime Rischard, Johanni Brea, Thomas Pinder

SGMCMCJax: a lightweight JAX library for stochastic gradient Markov chain Monte Carlo algorithms

Journal of Open Source Software

April 2022 · Jeremie Coullon, Christopher Nemeth

Gaussian processes on hypergraphs

arXiv preprint

June 2021 · Thomas Pinder, Kathryn Turnbull, Christopher Nemeth, David Leslie

A Probabilistic Assessment of the COVID-19 Lockdown on Air Quality in the UK

arXiv preprint

April 2021 · Thomas Pinder, Michael Hollaway, Christopher Nemeth, Paul J Young, David Leslie

Stochastic Gradient Markov Chain Monte Carlo

Journal of the American Statistical Association

January 2021 · Christopher Nemeth, Paul Fearnhead

Stein variational Gaussian processes

arXiv preprint

September 2020 · Thomas Pinder, Christopher Nemeth, David Leslie

Bayesian calibration of firn densification models

The Cryosphere

September 2020 · Vincent Verjans, Amber A Leeson, Christopher Nemeth, C Max Stevens, Peter Kuipers Munneke, Brice Noel, Jan Melchior Van Wessem

Pseudo-extended Markov chain Monte Carlo

Neural Information Processing Systems (NeurIPS)

December 2019 · Christopher Nemeth, Fredrik Lindsten, Maurizio Filippone, James Hensman

sgmcmc: An R package for stochastic gradient Markov chain Monte Carlo

Journal of Statistical Software

October 2019 · Jack Baker, Paul Fearnhead, Emily B Fox, Christopher Nemeth

Control variates for stochastic gradient MCMC

Statistics and Computing

May 2019 · Jack Baker, Paul Fearnhead, Emily B Fox, Christopher Nemeth

Large-Scale Stochastic Sampling from the Probability Simplex

Neural Information Processing Systems (NeurIPS)

December 2018 · Jack Baker, Paul Fearnhead, Emily B Fox, Christopher Nemeth

Merging MCMC Subposteriors through Gaussian-Process Approximations

Bayesian Analysis

June 2018 · Christopher Nemeth, Chris Sherlock