November 24th 3-4pm PSC A54
Francois-Xavier Briol Statistical Inference for Generative Models with Maximum Mean Discrepancy [Abstract]
October 9th 1.30pm-2.30pm PSC A54
Magnus Rattray Using Gaussian processes to infer pseudotime and branching from single-cell data. [Abstract]
September 20th 3pm-4pm PSC A54
Sam Livingstone On the robustness of gradient-based MCMC algorithms. [Abstract]
August 1st 3pm-4pm STOR-i Hub
Leah South Variance reduction in MCMC.
June 13th 3pm-4pm PSC A54
Clement Lee Clustering approach and MCMC practicalities of stochastic block models.[Abstract]
May 9th 3pm-4pm PSC A54
Nick Tawn The Annealed Leap Point Sampler (ALPS) for multimodal target distributions.[Abstract]
March 28th, 3pm-4pm STOR-i Hub
Callum Vyner An Introduction to Divide-and-Conquer MCMC.
February 28th, 3pm-4pm PSC A54
Matthew Ludkin Hug ‘N’ Hop: Explicit, non-reversible, contour-hugging MCMC.
February 14th, 3pm-4pm STOR-i Boardroom
Henry Moss An Intro to Information-Driven Bayesian Optimisation
December 13th, 3pm-4pm PSC A54
Arnaud Doucet On discrete-time piecewise-deterministic MCMC schemes
December 5th, 3pm-4pm PSC A54
Louis Aslett Privacy and Security in Bayesian Inference
November 15th, 3pm-4pm PSC A54
Chris Sherlock The Minimal Extended Statespace Algorithm for exact inference on Markov jump processes
Decmber 7th, 3pm-4pm PSC A54
Gareth Ridall Sequential Bayesian estimation and model selection [Abstract]
November 29th, 11am-12pm PSC A54
Chris Nemeth Pseudo-extended MCMC [Abstract]
November 9th, 3pm-4pm PSC A54
Luke Kelly Lateral trait transfer in phylogenetic inference [Abstract]
November 1st, 2pm-3pm PSC A54
Yee Whye Teh On Bayesian Deep Learning and Deep Bayesian Learning [Abstract]
May 18th, 2pm-4pm PSC A54
Chris Sherlock Asymptotic variance and geometric convergence of MCMC: variational representations [Abstract]
January 26th, 2pm PSC A54
Chris Sherlock Delayed-acceptance MCMC with examples: advantages and pitfalls and how to avoid the latter [Abstract]
December 6th, 2pm PSC A54
Jack Baker An overview of Bayesian non-parametrics.
November 11th, 2pm PSC A54
Wentao Li Improved Convergence of Regression Adjusted Approximate Bayesian Computation.
October 20th, 2pm PSC Lab2
Paul Fearnhead The Scalable Langevin Exact Algorithm: Bayesian Inference for Big Data.
July 2nd, 2pm B49
Adam Johansen The iterated auxiliary particle filter.
May 19th, 2pm PSC Lab2
Chris Sherlock Pseudo-marginal MCMC using averages of unbiased estimators.
May 9th, 2pm PSC LT
Joris Bierkens (Warwick University) Super-efficient sampling using Zig Zag Monte Carlo.
April 14th, 2pm PSC Lab1
Paul Fearnhead Research opportunities with MCMC and Big Data.
March 17th, 2pm PSC LT
Peter Neal Optimal scaling of the independence sampler.
February 25th, 2pm PSC LT
Paul Fearnhead Continuous-Time Importance Sampling (and MCMC).
February 18th, 2pm PSC LT
Borja de Balle Pigem Differentially Private Policy Evaluation.
December 10th, 2pm PSC LT
Jack Baker STAN
November 26th, 2pm PSC Lab2
Paul Fearnhead Discussion of “The Bouncy Particle Sampler: A Non-Reversible Rejection-Free Markov Chain Monte Carlo Method” [arXiv] and of “A Markov Jump Process for More Efficient Hamiltonian Monte Carlo” [arXiv].
October 15th, 2pm PSC LT.
James Hensman. Variational inference in Gaussian process models.
May 19th, 12pm PSC LT.
Alexandre Thiery (National University of Singapore). Asymptotic Analysis of Random-Walk Metropolis on Ridged Densities.
April 28th, 1pm PSC LT.
Chris Sherlock. Delayed acceptance particle marginal random walk Metropolis algorithms and their optimisation.
March 5th, 2pm PSC LT.
Chris Nemeth. Bayesian Inference for Big Data: Current and Future Directions.
Decmber 18th, 2pm PSC LT.
Wentao Li. Discussion of the RSS read paper: “Sequential Quasi Monte Carlo” by Mathieu Gerber and Nicolas Chopin.
November 28th, 11am PSC LT.
Chris Nemeth. Particle Metropolis adjusted Langevin algorithms.
March 11th, 2pm PSC LT.
Paul Fearnhead. Reparameterisations for Particle MCMC.
February 25th, 2pm PSC LT.
Vasileios Maroulas (University of Tennessee). Filtering, drift homotopy and target tracking.
Dember 11th, 1pm PSC LT.
Dennis Prangle (Universtity of Bristol). Speeding ABC inference using early-stopping simulations.
May 9th, 2pm PSC LT.
Chris Sherlock. Properties and Optimisation of the Pseudo Marginal RWM.
April 17th, 2pm PSC LT.
Anthony Lee (University of Warwick). Particle Markov chain Monte Carlo and marginal likelihood estimation: strategies for improvement.
Dennis Prangle. Likelihood-free parameter estimation for state space models
Joe Mellor (University of Manchester). Thompson Sampling in Switching Environments with Bayesian Online Change Point Detection
June 21st, 12.00pm (A54 Lecture Theatre) Classification in Dynamic Streaming Environments - Nicos Pavlidis (Dept of Management Science, Lancaster University).
June 6th, 12.00pm (A54 Lecture Theatre) Hamiltonian Monte Carlo: Beyond Kinetic Energy - Paul Fearnhead.
May 22nd, 12.00pm (A54 Lecture Theatre) Metropolis Adjusted Langevin Algorithm (MALA), simplified Manifold MALA, and Hamiltonian Monte Carlo: motivation, explanation and application - Chris Sherlock.
February 14th, 12.00pm (A54 Lecture Theatre) Summary statistics for ABC model choice - Dennis Prangle.
Decmber 13th, 3.00pm (A54 Lecture Theatre) Constructing summary statistics for approximate Bayesian computation: semi-automatic ABC - Paul Fearnhead. [arXiv].
November 16th, 12.00pm (B35 John Nelder Room) High-dimensional variable selection via tilting - Haeran Cho (London School of Economics).
June 17th, 12.00pm (Lab1 PSC) Online inference and model selection using sequential Monte Carlo - Gareth Ridall.
May 24th, 12.00pm (A54 Lecture Theatre) Simulation of mixed speed biochemical reactions using the linear noise approximation - Chris Sherlock
March 15th, 12.00pm (Lab1 PSC) Reading group on “An explicit link between Gaussian fields and Gaussian Markov random fields: The SPDE approach” - led by Paul Fearnhead. Preprint.
February 15th, 12.15pm (Lab1 PSC) Quantum Monte Carlo - Neil Drummond (Dept of Physics, Lancaster University)
January 18th, 1.00pm (A54 Lecture Theatre) Optimal detection of changepoints with a linear computational cost - Rebecca Killick
Decmember 7th, 12.00pm (A54 Lecture Theatre) Using ABC for sequential Bayesian analysis - Dennis Prangle.
November 10th, 12.00pm (A54 Lecture Theatre) Exact Inference for a Markov switching diffusion model with discretely observed data - Krzysztof Latuszynski (University of Warwick).
November 3rd, 12.00pm (A54 Lecture Theatre) Bayesian variable selection using Lasso - Anastasia Lykou.
October 10th, 12.00pm (A54 Lecture Theatre) Reading group on “Riemann manifold Langevin and Hamiltonian Monte Carlo methods” - led by Paul Fearnhead. [arXiv].
September 3rd, 1pm Particle Filters for models with fixed parameters - Paul Fearnhead
February 16th Reading group on Particle MCMC and the pseudo marginal algorithm - led by Gareth Ridall. Giorgos’ guide to the pseudo marginal algorithm;
December 1st (lab1 PSC) - The random walk Metropolis: general criteria for the 0.234 acceptance rate rule - Chris Sherlock
November 3rd - Likelihood based inference for discretely observed diffusions - Giorgos Sermaidis
October 20th - Sequential Importance Sampling for General Diffusion Models - Paul Fearnhead