Institute for Mathematical Sciences

Bayesian Computation for High-Dimensional Statistical Models

(27 Aug - 21 Sep 2018)

Visitor List

O. Deniz Akyildiz
Universidad Carlos III de Madrid, Spain
Khaled Alrajhi
King Khalid University, Saudi Arabia
Christophe Andrieu
University of Bristol, UK

TBA

Alexandros Beskos
University College London, UK
Adrian Bishop
Data61/CSIRO and University of Technology Sydney, Australia

On some stability and uniform fluctuation estimates of ensemble Kalman-Bucy filters

Neil Chada
National University of Singapore, Singapore
Hock Peng Chan
National University of Singapore, Singapore
Ngoc Huy Chau
Alfréd Rényi Institute of Mathematics, Budapest, Hungary
Sanjay Chaudhuri
National University of Singapore, Singapore
Taeryon Choi
Korea University, Korea

High-dimensional Bayesian semiparametric quantile models

Yunjin Choi
National University of Singapore, Singapore
Nawinda Chutsagulprom
Chiang Mai University, Thailand
Dan Crisan
Imperial College London, UK

Particle filters in high dimensions

Tiangang Cui
Monash University, Australia

Optimisation-based sampling approaches for hierarchical Bayesian inference

Pierre Del Moral
Institut National de Recherche en Informatique et en Automatique, France

A duality formula and a particle Gibbs sampler for continuous time Feynman-Kac measures on path spaces

George Deligiannidis
University of Oxford, UK
Dyah Ekashanti Octorina Dewi
Universiti Teknologi Malaysia, Malaysia
Arnaud Doucet
Oxford University, UK

TBA

Christopher Drovandi
Queensland University of Technology Brisbane, Australia

Extending simulation-based Bayesian inference to higher dimensions

Jin-Chuan Duan
National University of Singapore, Singapore
Markus Eisenbach
Oak Ridge National Laboratory, USA

Histogram-free multicanonical Monte Carlo Sampling method for statistical physics of systems with continous phase space

Axel Finke
National University of Singapore, Singapore
Neil Foster
University College London, UK
Jordan Franks
University of Jyväskylä, Finland
Matthew Graham
National University of Singapore, Singapore
Jeremy Heng
Harvard University, USA

Unbiased Hamiltonian Monte Carlo with couplings

Jeremie Houssineau
National University of Singapore, Singapore
Maria De Iorio
University College London, UK

Bayesian nonparametric autoregressive models via latent variable representation

Ajay Jasra
National University of Singapore, Singapore
Kengo Kamatani
Osaka University, Japan
Nikolas Kantas
Imperial College London, UK

Particle filtering for stochastic Navier-Stokes signal observed with additive noise

Robert Kohn
University of New South Wales, Australia

Efficiently combining pseudo marginal and particle Gibbs sampling

Kody Law
The University of Manchester, UK

TBA

Anthony Lee
University of Bristol, UK

Variance estimation in the particle filter

Cheng Li
National University of Singapore, Singapore
Jinglai Li
Shanghai Jiaotong University, China
Vasileios Maroulas
University of Tennessee, USA

TBA

Gael M. Martin
Monash University, Australia

Approximate Bayesian forecasting

Youssef M. Marzouk
Massachusetts Institute of Technology, USA

TBA

Joaquín Míguez
Universidad Carlos III de Madrid, Spain

TBA

Aleksandar Mijatović
King's College London, UK

TBA

Eric Moulines
École Polytechnique, France

Langevin MCMC: theory and methods

Lawrence Murray
Uppsala University, Sweden

Delayed sampling and automatic Rao-Blackwellization of probabilistic programs

Duc Quang Nguyen
Singapore Eye Research Institute, Singapore
David Nott
National University of Singapore, Singapore
Yasuhiro Omori
University of Tokyo, Japan

Particle rolling MCMC with double block sampling: conditional SMC update approach

Chananun Onjan
Chiang Mai University, Thailand
Siti Norhidayah Binti Othman
Ewha Womans University , Republic of Korea
Ni Luh Putu Satyaning Pradnya Paramita
Institute Teknologi Sepuluh Nopember, Indonesia
Daniel Paulin
University of Oxford, UK
Parkpoom Phetpradap
Chiang Mai University, Thailand
Michael Pitt
King's College London, UK

TBA

Sebastian Reich
Universität Potsdam, Germany

Filtering and smoothing through Lagrangian interacting particle representations

Christian Robert
University of Warwick, UK and Université Paris-Dauphine, France

Approximate Bayesian computation with the Wasserstein distance

Lassi Roininen
University of Oulu, Finland
Patrick Rubin-Delanchy
University of Bristol, UK

Spectral embedding of networks

Torben Sell
University of Cambridge, UK
Alexander Shestopaloff
The Alan Turing Institute, UK
Sumeetpal Singh
University of Cambridge, UK

The coupled conditional backward sampling particle filter

Xiaolin Song
Osaka University, Japan
Phisiphong Sonprathet
Chiang Mai University, Thailand
Linda, Siew Li Tan
National University of Singapore, Singapore
Terence Tan
DSO National Laboratories, Singapore
Thitiya Theparod
Mahasarakham University, Thailand
Alexandre Thiery
National University of Singapore, Singapore
Denis Tkachenko
National University of Singapore, Singapore
Xin Tong
National University of Singapore, Singapore
Ngoc Lan Trinh Thi
Ha Noi University of Science, Vietnam
Willem van den Boom
National University of Singapore, Singapore
Matti Vihola
University of Jyväskylä, Finland

Importance sampling type estimators based on approximate marginal MCMC

Ba-Ngu Vo
Curtin University, Australia

High-dimensional Inferencing for multi-object dynamical systems

Manav Vohra
The University of Texas at Austin, USA
Junjie Wang
Harbin Institute of Technology, China
Nick Whiteley
University of Bristol, UK

The Viterbi process and parallelized estimation in high-dimensions

Shouto Yonekura
University College London, UK
Fangyuan Yu
National University of Singapore, Singapore