Tuning-Free Maximum Likelihood Training of Latent Variable Models via Coin Betting
International Conference on Artificial Intelligence and Statistics (AISTATS)
Spatial Latent Gaussian Modelling with Change of Support
arXiv preprint
Latent space modelling of hypergraph data
Journal of the American Statistical Association
SwISS: A scalable Markov chain Monte Carlo divide-and-conquer strategy
Stat
Learning Rate Free Sampling in Constrained Domains
Neural Information Processing Systems (NeurIPS)
Characterising the ice sheet surface in Northeast Greenland using Sentinel-1 SAR data
Journal of Glaciology
Coin Sampling: Gradient-Based Bayesian Inference without Learning Rates
International Conference on Machine Learning (ICML)
Preferential Subsampling for Stochastic Gradient Langevin Dynamics
International Conference on Artificial Intelligence and Statistics (AISTATS)
Transport Elliptical Slice Sampling
International Conference on Artificial Intelligence and Statistics (AISTATS)
Multivariate sensitivity analysis for a large-scale climate impact and adaptation model
Journal of the Royal Statistical Society: Series C
Efficient and generalizable tuning strategies for stochastic gradient MCMC
Statistics and Computing
Sequential Estimation of Temporally Evolving Latent Space Network Models
Computational Statistics and Data Analysis
Distances for Comparing Multisets and Sequences
arXiv preprint
Semi-exact control functionals from Sard’s method
Biometrika
GaussianProcesses.jl: A Nonparametric Bayes Package for the Julia Language
Journal of Statistical Software
SGMCMCJax: a lightweight JAX library for stochastic gradient Markov chain Monte Carlo algorithms
Journal of Open Source Software
Gaussian processes on hypergraphs
arXiv preprint
A Probabilistic Assessment of the COVID-19 Lockdown on Air Quality in the UK
arXiv preprint
Stochastic Gradient Markov Chain Monte Carlo
Journal of the American Statistical Association
Stein variational Gaussian processes
arXiv preprint