Accelerating Bayesian Inference over Nonlinear Differential Equations with Gaussian Processes. - Ben Calderhead; Mark A. Girolami; Neil D. Lawrence (NIPS, 2008)

Estimating Bayes factors via thermodynamic integration and population MCMC. - Ben Calderhead; Mark A. Girolami (Comput. Stat. Data Anal., 2009)

System Identification and Model Ranking: The Bayesian Perspective. - Mark Girolami; Ben Calderhead; Vladislav Vyshemirsky (Learning and Inference in Computational Systems Biology, 2010)

Sparse Approximate Manifolds for Differential Geometric MCMC. - Ben Calderhead; Mátyás A. Sustik (NIPS, 2012)

Hamiltonian Monte Carlo methods for efficient parameter estimation in steady state dynamical systems. - Andrei Kramer; Ben Calderhead; Nicole Radde (BMC Bioinform., 2014)

Ten Simple Rules for Effective Computational Research. - James M. Osborne; Miguel O. Bernabeu; Maria Bruna; Ben Calderhead; Jonathan Cooper; Neil Dalchau; Sara-Jane Dunn; Alexander G. Fletcher; Robin Freeman; Derek Groen; Bernhard Knapp; Greg J. McInerny; et al. (PLoS Comput. Biol., 2014)

Ten Simple Rules for a Successful Cross-Disciplinary Collaboration. - Bernhard Knapp; Rémi Bardenet; Miguel O. Bernabeu; Rafel Bordas; Maria Bruna; Ben Calderhead; Jonathan Cooper; Alexander G. Fletcher; Derek Groen; Bram Kuijper; Joanna Lewis; Greg J. McInerny; et al. (PLoS Comput. Biol., 2015)

Probabilistic Linear Multistep Methods. - Onur Teymur; Konstantinos Zygalakis; Ben Calderhead (NIPS, 2016)

Implicit Probabilistic Integrators for ODEs. - Onur Teymur; Han Cheng Lie; Tim Sullivan 001; Ben Calderhead (NeurIPS, 2018)

Efficient structure learning with automatic sparsity selection for causal graph processes. - Théophile Griveau-Billion; Ben Calderhead (CoRR, 2019)

Rao-Blackwellised parallel MCMC. - Tobias Schwedes; Ben Calderhead (AISTATS, 2021)