Girolami, Mark

29 publications

JMLR 2025 Autoencoders in Function Space Justin Bunker, Mark Girolami, Hefin Lambley, Andrew M. Stuart, T. J. Sullivan

NeurIPS 2024 Generating Origin-Destination Matrices in Neural Spatial Interaction Models Ioannis Zachos, Mark Girolami, Theodoros Damoulas

AISTATS 2024 Riemannian Laplace Approximation with the Fisher Metric Hanlin Yu, Marcelo Hartmann, Bernardo Williams Moreno Sanchez, Mark Girolami, Arto Klami

JMLR 2024 Targeted Separation and Convergence with Kernel Discrepancies Alessandro Barp, Carl-Johann Simon-Gabriel, Mark Girolami, Lester Mackey

TMLR 2024 Tweedie Moment Projected Diffusions for Inverse Problems Benjamin Boys, Mark Girolami, Jakiw Pidstrigach, Sebastian Reich, Alan Mosca, Omer Deniz Akyildiz

ICML 2023 Random Grid Neural Processes for Parametric Partial Differential Equations Arnaud Vadeboncoeur, Ieva Kazlauskaite, Yanni Papandreou, Fehmi Cirak, Mark Girolami, Omer Deniz Akyildiz

TMLR 2023 Sobolev Spaces, Kernels and Discrepancies over Hyperspheres Simon Hubbert, Emilio Porcu, Chris J. Oates, Mark Girolami

AISTATS 2022 Lagrangian Manifold Monte Carlo on Monge Patches Marcelo Hartmann, Mark Girolami, Arto Klami

NeurIPSW 2022 Targeted Separation and Convergence with Kernel Discrepancies Alessandro Barp, Carl-Johann Simon-Gabriel, Mark Girolami, Lester Mackey

JMLR 2021 Convergence Guarantees for Gaussian Process Means with Misspecified Likelihoods and Smoothness George Wynne, François-Xavier Briol, Mark Girolami

AISTATS 2020 Dynamic Content Based Ranking Seppo Virtanen, Mark Girolami

NeurIPS 2019 Minimum Stein Discrepancy Estimators Alessandro Barp, Francois-Xavier Briol, Andrew Duncan, Mark Girolami, Lester Mackey

NeurIPS 2019 Multi-Resolution Multi-Task Gaussian Processes Oliver Hamelijnck, Theodoros Damoulas, Kangrui Wang, Mark Girolami

NeurIPS 2019 Precision-Recall Balanced Topic Modelling Seppo Virtanen, Mark Girolami

ICML 2019 Stein Point Markov Chain Monte Carlo Wilson Ye Chen, Alessandro Barp, Francois-Xavier Briol, Jackson Gorham, Mark Girolami, Lester Mackey, Chris Oates

ICML 2018 Bayesian Quadrature for Multiple Related Integrals Xiaoyue Xi, Francois-Xavier Briol, Mark Girolami

ICML 2017 On the Sampling Problem for Kernel Quadrature François-Xavier Briol, Chris J. Oates, Jon Cockayne, Wilson Ye Chen, Mark Girolami

NeurIPS 2017 Probabilistic Models for Integration Error in the Assessment of Functional Cardiac Models Chris Oates, Steven Niederer, Angela Lee, François-Xavier Briol, Mark Girolami

NeurIPS 2015 Frank-Wolfe Bayesian Quadrature: Probabilistic Integration with Theoretical Guarantees François-Xavier Briol, Chris Oates, Mark Girolami, Michael A Osborne

ICML 2015 Ordinal Mixed Membership Models Seppo Virtanen, Mark Girolami

AISTATS 2012 Preface Neil D. Lawrence, Mark Girolami

NeurIPS 2009 Analysis of SVM with Indefinite Kernels Yiming Ying, Colin Campbell, Mark Girolami

AISTATS 2009 Reversible Jump MCMC for Non-Negative Matrix Factorization Mingjun Zhong, Mark Girolami

NeurIPS 2008 Accelerating Bayesian Inference over Nonlinear Differential Equations with Gaussian Processes Ben Calderhead, Mark Girolami, Neil D. Lawrence

NeurIPS 2006 Data Integration for Classification Problems Employing Gaussian Process Priors Mark Girolami, Mingjun Zhong

NeurIPS 2006 Kernel Maximum Entropy Data Transformation and an Enhanced Spectral Clustering Algorithm Robert Jenssen, Torbjørn Eltoft, Mark Girolami, Deniz Erdogmus

NeurIPS 2006 Sparse Multinomial Logistic Regression via Bayesian L1 Regularisation Gavin C. Cawley, Nicola L. Talbot, Mark Girolami

NeurIPS 2003 Simplicial Mixtures of Markov Chains: Distributed Modelling of Dynamic User Profiles Mark Girolami, Ata Kabán

AISTATS 1997 Multivariate Density Factorization for Independent Component Analysis: An Unsupervised Artificial Neural Network Approach Mark Girolami, Colin Fyfe