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
Bayesian calibration of firn densification models
The Cryosphere
Pseudo-extended Markov chain Monte Carlo
Neural Information Processing Systems (NeurIPS)
sgmcmc: An R package for stochastic gradient Markov chain Monte Carlo
Journal of Statistical Software
Control variates for stochastic gradient MCMC
Statistics and Computing
Large-Scale Stochastic Sampling from the Probability Simplex
Neural Information Processing Systems (NeurIPS)
Merging MCMC Subposteriors through Gaussian-Process Approximations
Bayesian Analysis
Particle approximations of the score and observed information matrix for parameter estimation in state–space models with linear computational cost
Journal of Computational and Graphical Statistics
Particle Metropolis-adjusted Langevin algorithms
Biometrika
Parameter estimation for state space models using sequential Monte Carlo algorithms
PhD Thesis
Sequential Monte Carlo methods for state and parameter estimation in abruptly changing environments
IEEE Transactions on Signal Processing
Bearings-only tracking with particle filtering for joint parameter learning and state estimation
15th International Conference on Information Fusion
Particle learning methods for state and parameter estimation
9th IET Data Fusion and Target Tracking Conference