Roberts, Stephen

21 publications

JMLR 2024 Iterate Averaging in the Quest for Best Test Error Diego Granziol, Nicholas P. Baskerville, Xingchen Wan, Samuel Albanie, Stephen Roberts

AISTATS 2022 Marginalising over Stationary Kernels with Bayesian Quadrature Saad Hamid, Sebastian Schulze, Michael A. Osborne, Stephen Roberts

JMLR 2022 Adversarial Robustness Guarantees for Gaussian Processes Andrea Patane, Arno Blaas, Luca Laurenti, Luca Cardelli, Stephen Roberts, Marta Kwiatkowska

JMLR 2022 Learning Rates as a Function of Batch Size: A Random Matrix Theory Approach to Neural Network Training Diego Granziol, Stefan Zohren, Stephen Roberts

ICML 2022 Stabilizing Off-Policy Deep Reinforcement Learning from Pixels Edoardo Cetin, Philip J Ball, Stephen Roberts, Oya Celiktutan

AISTATS 2021 Learning Bijective Feature Maps for Linear ICA Alexander Camuto, Matthew Willetts, Chris Holmes, Brooks Paige, Stephen Roberts

AISTATS 2021 Towards a Theoretical Understanding of the Robustness of Variational Autoencoders Alexander Camuto, Matthew Willetts, Stephen Roberts, Chris Holmes, Tom Rainforth

ICML 2021 Augmented World Models Facilitate Zero-Shot Dynamics Generalization from a Single Offline Environment Philip J Ball, Cong Lu, Jack Parker-Holder, Stephen Roberts

UAI 2021 Towards Tractable Optimism in Model-Based Reinforcement Learning Aldo Pacchiano, Philip Ball, Jack Parker-Holder, Krzysztof Choromanski, Stephen Roberts

AISTATS 2020 Adversarial Robustness Guarantees for Classification with Gaussian Processes Arno Blaas, Andrea Patane, Luca Laurenti, Luca Cardelli, Marta Kwiatkowska, Stephen Roberts

ICML 2020 Bayesian Optimisation over Multiple Continuous and Categorical Inputs Binxin Ru, Ahsan Alvi, Vu Nguyen, Michael A. Osborne, Stephen Roberts

ICMLW 2020 Effective Diversity in Population Based Reinforcement Learning Jack Parker-Holder, Aldo Pacchiano, Krzysztof Choromanski, Stephen Roberts

ICML 2020 Ready Policy One: World Building Through Active Learning Philip Ball, Jack Parker-Holder, Aldo Pacchiano, Krzysztof Choromanski, Stephen Roberts

ICLR 2020 Towards Understanding the True Loss Surface of Deep Neural Networks Using Random Matrix Theory and Iterative Spectral Methods Diego Granziol, Timur Garipov, Dmitry Vetrov, Stefan Zohren, Stephen Roberts, Andrew Gordon Wilson

ICML 2019 Asynchronous Batch Bayesian Optimisation with Improved Local Penalisation Ahsan Alvi, Binxin Ru, Jan-Peter Calliess, Stephen Roberts, Michael A. Osborne

ICLRW 2019 WiSE-ALE: Wide Sample Estimator for Aggregate Latent Embedding Shuyu Lin, Ronald Clark, Robert Birke, Niki Trigoni, Stephen Roberts

ICML 2018 Optimization, Fast and Slow: Optimally Switching Between Local and Bayesian Optimization Mark McLeod, Stephen Roberts, Michael A. Osborne

ICML 2015 Scalable Nonparametric Bayesian Inference on Point Processes with Gaussian Processes Yves-Laurent Kom Samo, Stephen Roberts

ICML 2015 Variational Inference for Gaussian Process Modulated Poisson Processes Chris Lloyd, Tom Gunter, Michael Osborne, Stephen Roberts

JMLR 2014 Efficient State-Space Inference of Periodic Latent Force Models Steven Reece, Siddhartha Ghosh, Alex Rogers, Stephen Roberts, Nicholas R. Jennings

AISTATS 2012 Bayesian Quadrature for Ratios Michael Osborne, Roman Garnett, Stephen Roberts, Christopher Hart, Suzanne Aigrain, Neale Gibson