. Stochastic Gradient MCMC for Nonlinear State Space Models. ArXiv (in submission), 2019.

Preprint Code

. GaussianProcesses.jl: A Nonparametric Bayes package for the Julia Language. ArXiv (in submission), 2018.


. Control Variates for Stochastic Gradient MCMC. Statistics and Computing (to appear), 2018.

Preprint Code

. Large-Scale Stochastic Sampling from the Probability Simplex. NeurIPS 2018, 2018.

Preprint PDF Code Poster

. sgmcmc: An R Package for Stochastic Gradient Markov Chain Monte Carlo. Journal of Statistical Software (to appear), 2018.

Preprint Code

. Merging MCMC Subposteriors through Gaussian-Process Approximations. Bayesian Analysis 13(2):507-530, 2018.

Preprint PDF

. Pseudo-extended Makov chain Monte Carlo. ArXiv (in submission), 2017.

Preprint Code

. 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, 25(4):1138-1157, 2016.

Preprint PDF Code

. Particle Metropolis-adjusted Langevin algorithm. Biometrika, 103(3):701-717, 2016.

Preprint PDF

. Sequential Monte Carlo Methods for State and Parameter Estimation in Abruptly Changing Environments. IEEE Transactions on Signal Processing, 62(5):1245-1255, 2014.

PDF Code

. Bearings-only tracking with particle filtering for joint parameter learning and state estimation. 15th International Conference on Information Fusion, Singapore, pp.824-831, 2012.


. Particle learning methods for state and parameter estimation. 9th IET Data Fusion and Target Tracking Conference, London, U.K., 2012.




A nonparametric Bayes package for the Julia language.

Stochastic gradient MCMC

An R package based on Tensorflow for stochastic gradient Monte Carlo sampling.