Stephen J. Roberts

ORCID

Publication Activity (10 Years)

Years Active: 1994-2024
Publications (10 Years): 155

Top Venues

Publications

Harry Coppock, George Nicholson, Ivan Kiskin, Vasiliki Koutra, Kieran Baker, Jobie Budd, Richard Payne, Emma Karoune, David Hurley, Alexander Titcomb, Sabrina Egglestone, Ana Tendero Cañadas, Lorraine Butler, Radka Jersakova, Jonathon Mellor, Selina Patel, Tracey Thornley, Peter Diggle, Sylvia Richardson, Josef Packham, Björn W. Schuller, Davide Pigoli, Steven G. Gilmour, Stephen J. Roberts, Christopher C. Holmes
Audio-based AI classifiers show no evidence of improved COVID-19 screening over simple symptoms checkers. Nat. Mac. Intell. 6 (2) (2024)
Wee Ling Tan, Stephen J. Roberts, Stefan Zohren
Deep Learning for Options Trading: An End-To-End Approach. CoRR (2024)
Xingyue Pu, Stephen J. Roberts, Xiaowen Dong, Stefan Zohren
Network Momentum across Asset Classes. CoRR (2023)
Wee Ling Tan, Stephen J. Roberts, Stefan Zohren
Spatio-Temporal Momentum: Jointly Learning Time-Series and Cross-Sectional Strategies. CoRR (2023)
Samuel Kessler, Adam D. Cobb, Tim G. J. Rudner, Stefan Zohren, Stephen J. Roberts
On Sequential Bayesian Inference for Continual Learning. CoRR (2023)
Julien Walden Huang, Stephen J. Roberts, Jan-Peter Calliess
On the Sample Complexity of Lipschitz Constant Estimation. Trans. Mach. Learn. Res. 2023 (2023)
Kieran Wood, Samuel Kessler, Stephen J. Roberts, Stefan Zohren
Few-Shot Learning Patterns in Financial Time-Series for Trend-Following Strategies. CoRR (2023)
Xingyue Pu, Stefan Zohren, Stephen J. Roberts, Xiaowen Dong
Learning to Learn Financial Networks for Optimising Momentum Strategies. CoRR (2023)
Scott Alexander Cameron, Arnu Pretorius, Stephen J. Roberts
Nonparametric Boundary Geometry in Physics Informed Deep Learning. NeurIPS (2023)
Samuel Kessler, Adam D. Cobb, Tim G. J. Rudner, Stefan Zohren, Stephen J. Roberts
On Sequential Bayesian Inference for Continual Learning. Entropy 25 (6) (2023)
Lawrence Wang, Stephen J. Roberts
SANE: The phases of gradient descent through Sharpness Adjusted Number of Effective parameters. CoRR (2023)
Samuel Kessler, Mateusz Ostaszewski, Michal Pawel Bortkiewicz, Mateusz Zarski, Maciej Wolczyk, Jack Parker-Holder, Stephen J. Roberts, Piotr Milos
The Effectiveness of World Models for Continual Reinforcement Learning. CoLLAs (2023)
Edoardo Cetin, Philip J. Ball, Stephen J. Roberts, Oya Çeliktutan
Stabilizing Off-Policy Deep Reinforcement Learning from Pixels. ICML (2022)
Saad Hamid, Sebastian Schulze, Michael A. Osborne, Stephen J. Roberts
Marginalising over Stationary Kernels with Bayesian Quadrature. AISTATS (2022)
Davide Pigoli, Kieran Baker, Jobie Budd, Lorraine Butler, Harry Coppock, Sabrina Egglestone, Steven G. Gilmour, Chris Holmes, David Hurley, Radka Jersakova, Ivan Kiskin, Vasiliki Koutra, Jonathon Mellor, George Nicholson, Joe Packham, Selina Patel, Richard Payne, Stephen J. Roberts, Björn W. Schuller, Ana Tendero Cañadas, Tracey Thornley, Alexander Titcomb
Statistical Design and Analysis for Robust Machine Learning: A Case Study from COVID-19. CoRR (2022)
Daniel Poh, Stephen J. Roberts, Stefan Zohren
Transfer Ranking in Finance: Applications to Cross-Sectional Momentum with Data Scarcity. CoRR (2022)
Björn W. Schuller, Anton Batliner, Shahin Amiriparian, Christian Bergler, Maurice Gerczuk, Natalie Holz, Pauline Larrouy-Maestri, Sebastian P. Bayerl, Korbinian Riedhammer, Adria Mallol-Ragolta, Maria Pateraki, Harry Coppock, Ivan Kiskin, Marianne Sinka, Stephen J. Roberts
The ACM Multimedia 2022 Computational Paralinguistics Challenge: Vocalisations, Stuttering, Activity, & Mosquitoes. CoRR (2022)
Jaleh Zand, Jack Parker-Holder, Stephen J. Roberts
On-the-fly Strategy Adaptation for ad-hoc Agent Coordination. AAMAS (2022)
Samuel Kessler, Piotr Milos, Jack Parker-Holder, Stephen J. Roberts
The Surprising Effectiveness of Latent World Models for Continual Reinforcement Learning. CoRR (2022)
Scott Alexander Cameron, Tyron Luke Cameron, Arnu Pretorius, Stephen J. Roberts
Robust and Scalable SDE Learning: A Functional Perspective. ICLR (2022)
Jaleh Zand, Jack Parker-Holder, Stephen J. Roberts
On-the-fly Strategy Adaptation for ad-hoc Agent Coordination. CoRR (2022)
Björn W. Schuller, Anton Batliner, Shahin Amiriparian, Christian Bergler, Maurice Gerczuk, Natalie Holz, Pauline Larrouy-Maestri, Sebastien P. Bayerl, Korbinian Riedhammer, Adria Mallol-Ragolta, Maria Pateraki, Harry Coppock, Ivan Kiskin, Marianne Sinka, Stephen J. Roberts
The ACM Multimedia 2022 Computational Paralinguistics Challenge: Vocalisations, Stuttering, Activity, & Mosquitoes. ACM Multimedia (2022)
Diego Granziol, Binxin Ru, Xiaowen Dong, Stefan Zohren, Michael A. Osborne, Stephen J. Roberts
Maximum Entropy Approach to Massive Graph Spectrum Learning with Applications. Algorithms 15 (6) (2022)
Yingchen Xu, Jack Parker-Holder, Aldo Pacchiano, Philip J. Ball, Oleh Rybkin, Stephen J. Roberts, Tim Rocktäschel, Edward Grefenstette
Learning General World Models in a Handful of Reward-Free Deployments. CoRR (2022)
Samuel Kessler, Jack Parker-Holder, Philip J. Ball, Stefan Zohren, Stephen J. Roberts
Same State, Different Task: Continual Reinforcement Learning without Interference. AAAI (2022)
Cong Lu, Philip J. Ball, Jack Parker-Holder, Michael A. Osborne, Stephen J. Roberts
Revisiting Design Choices in Offline Model Based Reinforcement Learning. ICLR (2022)
Jobie Budd, Kieran Baker, Emma Karoune, Harry Coppock, Selina Patel, Ana Tendero Cañadas, Alexander Titcomb, Richard Payne, David Hurley, Sabrina Egglestone, Lorraine Butler, Jonathon Mellor, George Nicholson, Ivan Kiskin, Vasiliki Koutra, Radka Jersakova, Rachel A. McKendry, Peter Diggle, Sylvia Richardson, Björn W. Schuller, Steven Gilmour, Davide Pigoli, Stephen J. Roberts, Josef Packham, Tracey Thornley, Chris C. Holmes
A large-scale and PCR-referenced vocal audio dataset for COVID-19. CoRR (2022)
Shuyu Lin, Ronald Clark, Niki Trigoni, Stephen J. Roberts
Uncertainty Estimation with a VAE-Classifier Hybrid Model. ICASSP (2022)
Harry Coppock, George Nicholson, Ivan Kiskin, Vasiliki Koutra, Kieran Baker, Jobie Budd, Richard Payne, Emma Karoune, David Hurley, Alexander Titcomb, Sabrina Egglestone, Ana Tendero Cañadas, Lorraine Butler, Radka Jersakova, Jonathon Mellor, Selina Patel, Tracey Thornley, Peter Diggle, Sylvia Richardson, Josef Packham, Björn W. Schuller, Davide Pigoli, Steven Gilmour, Stephen J. Roberts, Chris C. Holmes
Audio-based AI classifiers show no evidence of improved COVID-19 screening over simple symptoms checkers. CoRR (2022)
Kieran Wood, Sven Giegerich, Stephen J. Roberts, Stefan Zohren
Trading with the Momentum Transformer: An Intelligent and Interpretable Architecture. CoRR (2021)
Samuel Kessler, Jack Parker-Holder, Philip J. Ball, Stefan Zohren, Stephen J. Roberts
Same State, Different Task: Continual Reinforcement Learning without Interference. CoRR (2021)
Ivan Kiskin, Marianne Sinka, Adam D. Cobb, Waqas Rafique, Lawrence Wang, Davide Zilli, Benjamin Gutteridge, Rinita Dam, Theodoros Marinos, Yunpeng Li, Dickson Msaky, Emmanuel Kaindoa, Gerard Killeen, Eva Herreros-Moya, Kathy Willis, Stephen J. Roberts
HumBugDB: A Large-scale Acoustic Mosquito Dataset. NeurIPS Datasets and Benchmarks (2021)
Samuel Kessler, Vu Nguyen, Stefan Zohren, Stephen J. Roberts
Hierarchical Indian buffet neural networks for Bayesian continual learning. UAI (2021)
Alexander Camuto, Matthew Willetts, Chris C. Holmes, Brooks Paige, Stephen J. Roberts
Learning Bijective Feature Maps for Linear ICA. AISTATS (2021)
Saad Hamid, Sebastian Schulze, Michael A. Osborne, Stephen J. Roberts
Marginalising over Stationary Kernels with Bayesian Quadrature. CoRR (2021)
Philip J. Ball, Cong Lu, Jack Parker-Holder, Stephen J. Roberts
Augmented World Models Facilitate Zero-Shot Dynamics Generalization From a Single Offline Environment. ICML (2021)
Philip J. Ball, Stephen J. Roberts
: What is state of the art anyway? CoRR (2021)
Matthew Willetts, Alexander Camuto, Tom Rainforth, Stephen J. Roberts, Christopher C. Holmes
Improving VAEs' Robustness to Adversarial Attack. ICLR (2021)
Shaan Desai, Marios Mattheakis, David Sondak, Pavlos Protopapas, Stephen J. Roberts
Port-Hamiltonian Neural Networks for Learning Explicit Time-Dependent Dynamical Systems. CoRR (2021)
Daniel Poh, Bryan Lim, Stefan Zohren, Stephen J. Roberts
Enhancing Cross-Sectional Currency Strategies by Ranking Refinement with Transformer-based Architectures. CoRR (2021)
Ivan Kiskin, Marianne Sinka, Adam D. Cobb, Waqas Rafique, Lawrence Wang, Davide Zilli, Benjamin Gutteridge, Rinita Dam, Theodoros Marinos, Yunpeng Li, Dickson Msaky, Emmanuel Kaindoa, Gerard Killeen, Eva Herreros-Moya, Kathy J. Willis, Stephen J. Roberts
HumBugDB: A Large-scale Acoustic Mosquito Dataset. CoRR (2021)
Cong Lu, Philip J. Ball, Jack Parker-Holder, Michael A. Osborne, Stephen J. Roberts
Revisiting Design Choices in Model-Based Offline Reinforcement Learning. CoRR (2021)
Lewis Smith, Joost van Amersfoort, Haiwen Huang, Stephen J. Roberts, Yarin Gal
Can convolutional ResNets approximately preserve input distances? A frequency analysis perspective. CoRR (2021)
Kieran Wood, Stephen J. Roberts, Stefan Zohren
Slow Momentum with Fast Reversion: A Trading Strategy Using Deep Learning and Changepoint Detection. CoRR (2021)
Ivan Kiskin, Adam D. Cobb, Marianne Sinka, Kathy Willis, Stephen J. Roberts
Automatic Acoustic Mosquito Tagging with Bayesian Neural Networks. ECML/PKDD (4) (2021)
Philip J. Ball, Cong Lu, Jack Parker-Holder, Stephen J. Roberts
Augmented World Models Facilitate Zero-Shot Dynamics Generalization From a Single Offline Environment. CoRR (2021)
Jack Parker-Holder, Vu Nguyen, Shaan Desai, Stephen J. Roberts
Tuning Mixed Input Hyperparameters on the Fly for Efficient Population Based AutoRL. CoRR (2021)
Anup Aprem, Stephen J. Roberts
Optimal pricing in black box producer-consumer Stackelberg games using revealed preference feedback. Neurocomputing 437 (2021)
Arno Blaas, Stephen J. Roberts
The Effect of Prior Lipschitz Continuity on the Adversarial Robustness of Bayesian Neural Networks. CoRR (2021)
Andrea Patane, Arno Blaas, Luca Laurenti, Luca Cardelli, Stephen J. Roberts, Marta Kwiatkowska
Adversarial Robustness Guarantees for Gaussian Processes. CoRR (2021)
Shaan Desai, Marios Mattheakis, Hayden Joy, Pavlos Protopapas, Stephen J. Roberts
One-Shot Transfer Learning of Physics-Informed Neural Networks. CoRR (2021)
Jack Parker-Holder, Vu Nguyen, Shaan Desai, Stephen J. Roberts
Tuning Mixed Input Hyperparameters on the Fly for Efficient Population Based AutoRL. NeurIPS (2021)
Alexander Camuto, Matthew Willetts, Stephen J. Roberts, Chris C. Holmes, Tom Rainforth
Towards a Theoretical Understanding of the Robustness of Variational Autoencoders. AISTATS (2021)
Matthew Willetts, Stephen J. Roberts, Chris C. Holmes
Semi-Unsupervised Learning: Clustering and Classifying using Ultra-Sparse Labels. IEEE BigData (2020)
Alexander Camuto, Matthew Willetts, Umut Simsekli, Stephen J. Roberts, Chris C. Holmes
Explicit Regularisation in Gaussian Noise Injections. NeurIPS (2020)
Alexander Camuto, Matthew Willetts, Stephen J. Roberts, Chris C. Holmes, Tom Rainforth
Towards a Theoretical Understanding of the Robustness of Variational Autoencoders. CoRR (2020)
Arno Blaas, Andrea Patane, Luca Laurenti, Luca Cardelli, Marta Kwiatkowska, Stephen J. Roberts
Adversarial Robustness Guarantees for Classification with Gaussian Processes. AISTATS (2020)
Alexander Camuto, Matthew Willetts, Umut Simsekli, Stephen J. Roberts, Chris C. Holmes
Explicit Regularisation in Gaussian Noise Injections. CoRR (2020)
Jan-Peter Calliess, Stephen J. Roberts, Carl Edward Rasmussen, Jan M. Maciejowski
Lazily Adapted Constant Kinky Inference for nonparametric regression and model-reference adaptive control. Autom. 122 (2020)
Jack Parker-Holder, Vu Nguyen, Stephen J. Roberts
Provably Efficient Online Hyperparameter Optimization with Population-Based Bandits. NeurIPS (2020)
Bernardo Pérez Orozco, Stephen J. Roberts
Zero-shot and few-shot time series forecasting with ordinal regression recurrent neural networks. CoRR (2020)
Kyriakos Polymenakos, Luca Laurenti, Andrea Patane, Jan-Peter Calliess, Luca Cardelli, Marta Kwiatkowska, Alessandro Abate, Stephen J. Roberts
Safety Guarantees for Iterative Predictions with Gaussian Processes. CDC (2020)
Bin Xin Ru, Ahsan S. Alvi, Vu Nguyen, Michael A. Osborne, Stephen J. Roberts
Bayesian Optimisation over Multiple Continuous and Categorical Inputs. ICML (2020)
Jack Parker-Holder, Aldo Pacchiano, Krzysztof Marcin Choromanski, Stephen J. Roberts
Effective Diversity in Population Based Reinforcement Learning. NeurIPS (2020)
Bernardo Pérez Orozco, Stephen J. Roberts
Zero-shot and few-shot time series forecasting with ordinal regression recurrent neural networks. ESANN (2020)
Kyriakos Polymenakos, Nikitas Rontsis, Alessandro Abate, Stephen J. Roberts
SafePILCO: A Software Tool for Safe and Data-Efficient Policy Synthesis. QEST (2020)
Diego Granziol, Samuel Albanie, Xingchen Wan, Stephen J. Roberts
Explaining the Adaptive Generalisation Gap. CoRR (2020)
Alexander Camuto, Matthew Willetts, Brooks Paige, Chris C. Holmes, Stephen J. Roberts
Learning Bijective Feature Maps for Linear ICA. CoRR (2020)
Philip J. Ball, Jack Parker-Holder, Aldo Pacchiano, Krzysztof Choromanski, Stephen J. Roberts
Ready Policy One: World Building Through Active Learning. ICML (2020)
Kyriakos Polymenakos, Nikitas Rontsis, Alessandro Abate, Stephen J. Roberts
SafePILCO: a software tool for safe and data-efficient policy synthesis. CoRR (2020)
Shuyu Lin, Ronald Clark, Robert Birke, Sandro Schönborn, Niki Trigoni, Stephen J. Roberts
Anomaly Detection for Time Series Using VAE-LSTM Hybrid Model. ICASSP (2020)
Matthew Willetts, Xenia Miscouridou, Stephen J. Roberts, Chris C. Holmes
Relaxed-Responsibility Hierarchical Discrete VAEs. CoRR (2020)
Ivan Kiskin, Davide Zilli, Yunpeng Li, Marianne Sinka, Kathy Willis, Stephen J. Roberts
Bioacoustic detection with wavelet-conditioned convolutional neural networks. Neural Comput. Appl. 32 (4) (2020)
Daniel Poh, Bryan Lim, Stefan Zohren, Stephen J. Roberts
Building Cross-Sectional Systematic Strategies By Learning to Rank. CoRR (2020)
Jack K. Fitzsimons, Sebastian M. Schmon, Stephen J. Roberts
Implicit Priors for Knowledge Sharing in Bayesian Neural Networks. CoRR (2019)
Kyriakos Polymenakos, Luca Laurenti, Andrea Patane, Jan-Peter Calliess, Luca Cardelli, Marta Kwiatkowska, Alessandro Abate, Stephen J. Roberts
Safety Guarantees for Planning Based on Iterative Gaussian Processes. CoRR (2019)
Matthew Willetts, Alexander Camuto, Stephen J. Roberts, Chris C. Holmes
Regularising Deep Networks with DGMs. CoRR (2019)
Favour M. Nyikosa, Michael A. Osborne, Stephen J. Roberts
Adaptive Configuration Oracle for Online Portfolio Selection Methods. CoRR (2019)
Zihao Zhang, Stefan Zohren, Stephen J. Roberts
Deep Reinforcement Learning for Trading. CoRR (2019)
Diego Granziol, Robin Ru, Stefan Zohren, Xiaowen Dong, Michael A. Osborne, Stephen J. Roberts
A Maximum Entropy approach to Massive Graph Spectra. CoRR (2019)
Bryan Lim, Stefan Zohren, Stephen J. Roberts
Population-based Global Optimisation Methods for Learning Long-term Dependencies with RNNs. CoRR (2019)
Arno Blaas, Luca Laurenti, Andrea Patane, Luca Cardelli, Marta Kwiatkowska, Stephen J. Roberts
Robustness Quantification for Classification with Gaussian Processes. CoRR (2019)
Bryan Lim, Stefan Zohren, Stephen J. Roberts
Recurrent Neural Filters: Learning Independent Bayesian Filtering Steps for Time Series Prediction. CoRR (2019)
Shuyu Lin, Ronald Clark, Robert Birke, Niki Trigoni, Stephen J. Roberts
WiSE-ALE: Wide Sample Estimator for Aggregate Latent Embedding. DGS@ICLR (2019)
Diego Granziol, Bin Xin Ru, Stefan Zohren, Xiaowen Dong, Michael A. Osborne, Stephen J. Roberts
MEMe: An Accurate Maximum Entropy Method for Efficient Approximations in Large-Scale Machine Learning. Entropy 21 (6) (2019)
Matthew Willetts, Stephen J. Roberts, Christopher C. Holmes
Semi-Unsupervised Learning with Deep Generative Models: Clustering and Classifying using Ultra-Sparse Labels. CoRR (2019)
Kyriakos Polymenakos, Alessandro Abate, Stephen J. Roberts
Safe Policy Search Using Gaussian Process Models. AAMAS (2019)
Richard Everett, Adam D. Cobb, Andrew Markham, Stephen J. Roberts
Optimising Worlds to Evaluate and Influence Reinforcement Learning Agents. AAMAS (2019)
Shuyu Lin, Ronald Clark, Robert Birke, Niki Trigoni, Stephen J. Roberts
WiSE-VAE: Wide Sample Estimator VAE. CoRR (2019)
Glen Wright Colopy, Stephen J. Roberts, David A. Clifton
Gaussian Processes for Personalized Interpretable Volatility Metrics in the Step-Down Ward. IEEE J. Biomed. Health Informatics 23 (3) (2019)
Adam D. Cobb, Atilim Günes Baydin, Andrew Markham, Stephen J. Roberts
Introducing an Explicit Symplectic Integration Scheme for Riemannian Manifold Hamiltonian Monte Carlo. CoRR (2019)
Matthew Willetts, Alexander Camuto, Stephen J. Roberts, Chris C. Holmes
Disentangling Improves VAEs' Robustness to Adversarial Attacks. CoRR (2019)
Zihao Zhang, Stefan Zohren, Stephen J. Roberts
DeepLOB: Deep Convolutional Neural Networks for Limit Order Books. IEEE Trans. Signal Process. 67 (11) (2019)
Bryan Lim, Stefan Zohren, Stephen J. Roberts
Enhancing Time Series Momentum Strategies Using Deep Neural Networks. CoRR (2019)
Diego Granziol, Bin Xin Ru, Stefan Zohren, Xiaowen Dong, Michael A. Osborne, Stephen J. Roberts
MEMe: An Accurate Maximum Entropy Method for Efficient Approximations in Large-Scale Machine Learning. CoRR (2019)
Edwin Simpson, Steven Reece, Stephen J. Roberts
Bayesian Heatmaps: Probabilistic Classification with Multiple Unreliable Information Sources. CoRR (2019)
Ahsan S. Alvi, Bin Xin Ru, Jan Calliess, Stephen J. Roberts, Michael A. Osborne
Asynchronous Batch Bayesian Optimisation with Improved Local Penalisation. CoRR (2019)
Anup Aprem, Stephen J. Roberts
Optimal Pricing In Black Box Producer-Consumer Stackelberg Games Using Revealed Preference Feedback. MLSP (2019)
Jack K. Fitzsimons, AbdulRahman Al Ali, Michael A. Osborne, Stephen J. Roberts
A General Framework for Fair Regression. Entropy 21 (8) (2019)
Bin Xin Ru, Ahsan S. Alvi, Vu Nguyen, Michael A. Osborne, Stephen J. Roberts
Bayesian Optimisation over Multiple Continuous and Categorical Inputs. CoRR (2019)

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Publication Activity (10 Years)

Top Topics

Top Venues

Stephen J. Roberts