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papers

Publications (41)

stat.ME2017

Probabilistic Models for Integration Error in the Assessment of Functional Cardiac Models

Chris. J. Oates, Steven Niederer, Angela Lee +2

stat.ME2016

Unbiased local solutions of partial differential equations via the Feynman-Kac Identities

Jake Carson, Murray Pollock, Mark Girolami

stat.CO2016

Control Functionals for Quasi-Monte Carlo Integration

Chris. J. Oates, Mark Girolami

stat.CO2012

Lagrangian Dynamical Monte Carlo

Shiwei Lan, Vassilios Stathopoulos, Babak Shahbaba +1

stat.CO2013

Discussion of "Geodesic Monte Carlo on Embedded Manifolds"

Simon Byrne, Mark Girolami, Persi Diaconis +9

stat.CO2013

Geodesic Monte Carlo on Embedded Manifolds

Simon Byrne, Mark Girolami

stat.ME2018

Posterior Integration on a Riemannian Manifold

Chris. J. Oates, Alessandro Barp, Mark Girolami

stat.CO2018

Bayesian Quadrature for Multiple Related Integrals

Xiaoyue Xi, François-Xavier Briol, Mark Girolami

stat.CO2017

Geometric MCMC for Infinite-Dimensional Inverse Problems

Alexandros Beskos, Mark Girolami, Shiwei Lan +2

stat.CO2015

Discussion of "Sequential Quasi-Monte Carlo" by Mathieu Gerber and Nicolas Chopin

Chris. J. Oates, Daniel Simpson, Mark Girolami

stat.AP2018

Efficiency and robustness in Monte Carlo sampling of 3-D geophysical inversions with Obsidian v0.1.2: Setting up for success

Richard Scalzo, David Kohn, Hugo Olierook +4

stat.ME2017

Probabilistic Numerical Methods for PDE-constrained Bayesian Inverse Problems

Jon Cockayne, Chris Oates, Tim Sullivan +1

stat.ME2017

Probabilistic Numerical Methods for Partial Differential Equations and Bayesian Inverse Problems

Jon Cockayne, Chris Oates, Tim Sullivan +1

math.ST2014

Solving Large-Scale PDE-constrained Bayesian Inverse Problems with Riemann Manifold Hamiltonian Monte Carlo

Tan Bui-Thanh, Mark Girolami

stat.CO2018

On the Geometric Ergodicity of Hamiltonian Monte Carlo

Samuel Livingstone, Michael Betancourt, Simon Byrne +1

math.ST2016

Hyperpriors for Matérn fields with applications in Bayesian inversion

Lassi Roininen, Mark Girolami, Sari Lasanen +1

stat.ME2014

The Geometric Foundations of Hamiltonian Monte Carlo

M. J. Betancourt, Simon Byrne, Samuel Livingstone +1

stat.ME2012

Some discussions of D. Fearnhead and D. Prangle's Read Paper "Constructing summary statistics for approximate Bayesian computation: semi-automatic approximate Bayesian computation"

Christophe Andrieu, Simon Barthelme, Nicolas Chopin +11

cs.SE2014

Probabilistic Model Checking of DTMC Models of User Activity Patterns

Oana Andrei, Muffy Calder, Matthew Higgs +1

stat.CO2014

Information-geometric Markov Chain Monte Carlo methods using Diffusions

Samuel Livingstone, Mark Girolami

stat.ML2014

Pseudo-Marginal Bayesian Inference for Gaussian Processes

Maurizio Filippone, Mark Girolami

stat.CO2019

Posterior Inference for Sparse Hierarchical Non-stationary Models

Karla Monterrubio-Gómez, Lassi Roininen, Sara Wade +2

stat.AP2019

The synthesis of data from instrumented structures and physics-based models via Gaussian processes

Alastair Gregory, Din-Houn Lau, Mark Girolami +2

stat.ME2016

Control functionals for Monte Carlo integration

Chris J. Oates, Mark Girolami, Nicolas Chopin

stat.ME2015

On Russian Roulette Estimates for Bayesian Inference with Doubly-Intractable Likelihoods

Anne-Marie Lyne, Mark Girolami, Yves Atchadé +2

stat.ME2018

A Bayesian Conjugate Gradient Method

Jon Cockayne, Chris Oates, Ilse Ipsen +1

stat.ME2013

Langevin diffusions and the Metropolis-adjusted Langevin algorithm

Tatiana Xifara, Chris Sherlock, Samuel Livingstone +2

stat.AP2018

Bayesian Probabilistic Numerical Methods in Time-Dependent State Estimation for Industrial Hydrocyclone Equipment

Chris. J. Oates, Jon Cockayne, Robert G. Aykroyd +1

stat.ML2017

Probabilistic Integration: A Role in Statistical Computation?

François-Xavier Briol, Chris. J. Oates, Mark Girolami +2

stat.ME2019

Statistical Inference for Generative Models with Maximum Mean Discrepancy

Francois-Xavier Briol, Alessandro Barp, Andrew B. Duncan +1

stat.CO2017

A determinant-free method to simulate the parameters of large Gaussian fields

Louis Ellam, Heiko Strathmann, Mark Girolami +1

math.ST2017

Convergence Rates for a Class of Estimators Based on Stein's Method

Chris J. Oates, Jon Cockayne, François-Xavier Briol +1

stat.CO2015

Emulation of Higher-Order Tensors in Manifold Monte Carlo Methods for Bayesian Inverse Problems

Shiwei Lan, Tan Bui-Thanh, Mike Christie +1

stat.ME2015

Probability Measures for Numerical Solutions of Differential Equations

Patrick R. Conrad, Mark Girolami, Simo Särkkä +2

stat.CO2019

Hamiltonian Monte Carlo on Symmetric and Homogeneous Spaces via Symplectic Reduction

Alessandro Barp, Anthony Kennedy, Mark Girolami

stat.ME2015

Optimizing The Integrator Step Size for Hamiltonian Monte Carlo

M. J. Betancourt, Simon Byrne, Mark Girolami

stat.ML2015

Frank-Wolfe Bayesian Quadrature: Probabilistic Integration with Theoretical Guarantees

François-Xavier Briol, Chris J. Oates, Mark Girolami +1

stat.CO2012

A Bayesian Approach to Approximate Joint Diagonalization of Square Matrices

Mingjun Zhong, Mark Girolami

stat.ME2014

The Controlled Thermodynamic Integral for Bayesian Model Comparison

Chris J. Oates, Theodore Papamarkou, Mark Girolami

stat.ML2015

Unbiased Bayes for Big Data: Paths of Partial Posteriors

Heiko Strathmann, Dino Sejdinovic, Mark Girolami

stat.ME2013

Hamiltonian Monte Carlo for Hierarchical Models

M. J. Betancourt, Mark Girolami