A Probabilistic Resource Allocating Network for Novelty Detection. - Stephen J. Roberts; Lionel Tarassenko (Neural Comput., 1994)

Scale-space unsupervised cluster analysis. - Stephen J. Roberts (ICPR, 1996)

Parametric and non-parametric unsupervised cluster analysis. - Stephen J. Roberts (Pattern Recognit., 1997)

Bayesian Approaches to Gaussian Mixture Modeling. - Stephen J. Roberts; Dirk Husmeier; Iead Rezek; William D. Penny (IEEE Trans. Pattern Anal. Mach. Intell., 1998)

Stochastic complexity measures for physiological signal analysis. - Iead Rezek; Stephen J. Roberts (IEEE Trans. Biomed. Eng., 1998)

Neural networks for predicting Kaposi's sarcoma. - Dirk Husmeier; Gillian S. Patton; Myra O. McClure; John R. W. Harris; Stephen J. Roberts (IJCNN, 1999)

Dynamic logistic regression. - William D. Penny; Stephen J. Roberts (IJCNN, 1999)

EEG-based communication via dynamic neural network models. - William D. Penny; Stephen J. Roberts (IJCNN, 1999)

Dynamic Models for Nonstationary Signal Segmentation. - William D. Penny; Stephen J. Roberts (Comput. Biomed. Res., 1999)

Independent Component Analysis: A Flexible Nonlinearity and Decorrelating Manifold Approach. - Richard M. Everson; Stephen J. Roberts (Neural Comput., 1999)

An empirical evaluation of Bayesian sampling with hybrid Monte Carlo for training neural network classifiers. - Dirk Husmeier; William D. Penny; Stephen J. Roberts (Neural Networks, 1999)

Bayesian neural networks for classification: how useful is the evidence framework? - William D. Penny; Stephen J. Roberts (Neural Networks, 1999)

Independent Components Analysis. - Richard M. Everson; Stephen J. Roberts (Artificial Neural Networks in Biomedicine, 2000)

The Bayesian Paradigm: Second Generation Neural Computing. - William D. Penny; Dirk Husmeier; Stephen J. Roberts (Artificial Neural Networks in Biomedicine, 2000)

Maximum certainty data partitioning. - Stephen J. Roberts; Richard M. Everson; Iead Rezek (Pattern Recognit., 2000)

Inferring the eigenvalues of covariance matrices from limited, noisy data. - Richard M. Everson; Stephen J. Roberts (IEEE Trans. Signal Process., 2000)

Blind Source Separation for Non-Stationary Mixing. - Richard M. Everson; Stephen J. Roberts (J. VLSI Signal Process., 2000)

Minimum-Entropy Data Clustering Using Reversible Jump Markov Chain Monte Carlo. - Stephen J. Roberts; Christopher C. Holmes; Dave Denison (ICANN, 2001)

Mixtures of Independent Component Analysers. - Stephen J. Roberts; William D. Penny (ICANN, 2001)

A Probabilistic Approach to High-Resolution Sleep Analysis. - Peter Sykacek; Stephen J. Roberts; Iead Rezek; Arthur Flexer; Georg Dorffner (ICANN, 2001)

Bayesian time series classification. - Peter Sykacek; Stephen J. Roberts (NIPS, 2001)

Minimum-Entropy Data Partitioning Using Reversible Jump Markov Chain Monte Carlo. - Stephen J. Roberts; Christopher C. Holmes; Dave Denison (IEEE Trans. Pattern Anal. Mach. Intell., 2001)

Ensemble hidden Markov models for biosignal analysis. - Iead Rezek; Stephen J. Roberts (DSP, 2002)

Adaptive Classification by Variational Kalman Filtering. - Peter Sykacek; Stephen J. Roberts (NIPS, 2002)

Towards the automatic analysis of complex human body motions. - Jens Rittscher; Andrew Blake 001; Stephen J. Roberts (Image Vis. Comput., 2002)

Variational Bayes for generalized autoregressive models. - Stephen J. Roberts; Will D. Penny (IEEE Trans. Signal Process., 2002)

Maximum a Posteriori Estimation of Coupled Hidden Markov Models. - Iead Rezek; Michael Gibbs; Stephen J. Roberts (J. VLSI Signal Process., 2002)

Ensemble Coupled Hidden Markov Models for Joint Characterisation of Dynamic Signals. - Iead Rezek; Stephen J. Roberts; Peter Sykacek (AISTATS, 2003)

Markov Models for Automated ECG Interval Analysis. - Nicholas P. Hughes; Lionel Tarassenko; Stephen J. Roberts (NIPS, 2003)

A Sampled Texture Prior for Image Super-Resolution. - Lyndsey C. Pickup; Stephen J. Roberts; Andrew Zisserman (NIPS, 2003)

Variational Mixture of Bayesian Independent Component Analyzers. - Rizwan Choudrey; Stephen J. Roberts (Neural Comput., 2003)

Data decomposition using independent component analysis with prior constraints. - Stephen J. Roberts; Rizwan Choudrey (Pattern Recognit., 2003)

Gene ranking using bootstrapped P-values. - S. N. Mukherjee; Stephen J. Roberts; Peter Sykacek; Sarah J. Gurr (SIGKDD Explor., 2003)

A Theoretical Analysis of Gene Selection. - Sach Mukherjee; Stephen J. Roberts (CSB, 2004)

Probabilistic Consistency Analysis for Gene Selection. - Sach Mukherjee; Stephen J. Roberts (CSB, 2004)

Bayesian Independent Component Analysis with Prior Constraints: An Application in Biosignal Analysis. - Stephen J. Roberts; Rizwan Choudrey (Deterministic and Statistical Methods in Machine Learning, 2004)

Hierarchy, priors and wavelets: structure and signal modelling using ICA. - Stephen J. Roberts; Evangelos Roussos; Rizwan Choudrey (Signal Process., 2004)

Adaptive BCI based on variational Bayesian Kalman filtering: an empirical evaluation. - Peter Sykacek; Stephen J. Roberts; Maria Stokes (IEEE Trans. Biomed. Eng., 2004)

Data-adaptive test statistics for microarray data. - Sach Mukherjee; Stephen J. Roberts; Mark J. van der Laan (ECCB/JBI, 2005)

Depth of anaesthesia assessment with generative polyspectral models. - Iead Rezek; Stephen J. Roberts; Ellini Siva; R. Conradt (ICMLA, 2005)

A Simple, Quasi-linear, Discrete Model of Vocal Fold Dynamics. - Max A. Little; Patrick E. McSharry; Irene M. Moroz; Stephen J. Roberts (NOLISP, 2005)

A Theoretical Analysis of the Selection of Differentially Expressed Genes. - Sach Mukherjee; Stephen J. Roberts (J. Bioinform. Comput. Biol., 2005)

Computational mechanism design for multi-sensor information fusion. - Alex Rogers; Rajdeep K. Dash; Nicholas R. Jennings; Steven Reece; Stephen J. Roberts (AAMAS, 2006)

Optimizing and Learning for Super-resolution. - Lyndsey C. Pickup; Stephen J. Roberts; Andrew Zisserman (BMVC, 2006)

Computational Mechanism Design for Information Fusion within Sensor Networks. - Alex Rogers; Rajdeep K. Dash; Nick R. Jennings; Steven Reece; Stephen J. Roberts (FUSION, 2006)

Nonlinear, Biophysically-Informed Speech Pathology Detection. - Max A. Little; Patrick E. McSharry; Irene M. Moroz; Stephen J. Roberts (ICASSP (2), 2006)

Bayesian Image Super-resolution, Continued. - Lyndsey C. Pickup; David P. Capel; Stephen J. Roberts; Andrew Zisserman (NIPS, 2006)

A Multi-Dimensional Trust Model for Heterogeneous Contract Observations. - Steven Reece; Stephen J. Roberts; Alex Rogers; Nicholas R. Jennings (AAAI, 2007)

Rumours and reputation: evaluating multi-dimensional trust within a decentralised reputation system. - Steven Reece; Alex Rogers; Stephen J. Roberts; Nicholas R. Jennings (AAMAS, 2007)

An Iterative Signal Detection Algorithm Based on Bayesian Belief Propagation Ideas. - Ian K. Proudler; Stephen Roberts 001; Steven Reece; Iead Rezek (DSP, 2007)

Drum'n'Bayes: on-Line variational Inference for beat tracking and rhythm Recognition. - Charles W. Fox; Iead Rezek; Stephen J. Roberts (ICMC, 2007)

Overcoming Registration Uncertainty in Image Super-Resolution: Maximize or Marginalize? - Lyndsey C. Pickup; David P. Capel; Stephen J. Roberts; Andrew Zisserman (EURASIP J. Adv. Signal Process., 2007)

Gene Microarray Analysis Using Angular Distribution Decomposition. - Karen Lees; Stephen J. Roberts; Pari Skamnioti; Sarah J. Gurr (J. Comput. Biol., 2007)

Decentralized predictive sensor allocation. - Mark Ebden; Mark Briers; Stephen J. Roberts (CDC, 2008)

On-line novelty detection using the Kalman filter and extreme value theory. - Hyoungjoo Lee; Stephen J. Roberts (ICPR, 2008)

Adaptive Classification by Hybrid EKF with Truncated Filtering: Brain Computer Interfacing. - Ji Won Yoon; Stephen J. Roberts; Matthew Dyson; John Q. Gan (IDEAL, 2008)

Towards Real-Time Information Processing of Sensor Network Data Using Computationally Efficient Multi-output Gaussian Processes. - Michael A. Osborne; Stephen J. Roberts; Alex Rogers; Sarvapali D. Ramchurn; Nicholas R. Jennings (IPSN, 2008)

Sequential Bayesian estimation for adaptive classification. - Ji Won Yoon; Stephen J. Roberts; Matthew Dyson; John Q. Gan (MFI, 2008)

Information Agents for Pervasive Sensor Networks. - Alex Rogers; Mike Osborne; Sarvapali D. Ramchurn; Stephen J. Roberts; Nicholas R. Jennings (PerCom, 2008)

On Similarities between Inference in Game Theory and Machine Learning. - Iead Rezek; David S. Leslie; Steven Reece; Stephen J. Roberts; Alex Rogers; Rajdeep K. Dash; Nicholas R. Jennings (J. Artif. Intell. Res., 2008)

Multi-sensor fault recovery in the presence of known and unknown fault types. - Steven Reece; Stephen J. Roberts; Christopher Claxton; David Nicholson (FUSION, 2009)

Sequential Bayesian prediction in the presence of changepoints. - Roman Garnett; Michael A. Osborne; Stephen J. Roberts (ICML, 2009)

Bayesian Methods for Image Super-Resolution. - Lyndsey C. Pickup; David P. Capel; Stephen J. Roberts; Andrew Zisserman (Comput. J., 2009)

A self-paced brain-computer interface for controlling a robot simulator: an online event labelling paradigm and an extended Kalman filter based algorithm for online training. - Chun Sing Louis Tsui; John Q. Gan; Stephen J. Roberts (Medical Biol. Eng. Comput., 2009)

Adaptive classification for Brain Computer Interface systems using Sequential Monte Carlo sampling. - Ji Won Yoon; Stephen J. Roberts; Matthew Dyson; John Q. Gan (Neural Networks, 2009)

Active Data Selection for Sensor Networks with Faults and Changepoints. - Michael A. Osborne; Roman Garnett; Stephen J. Roberts (AINA, 2010)

An introduction to Gaussian processes for the Kalman filter expert. - Steven Reece; Stephen J. Roberts (FUSION, 2010)

Bayesian optimization for sensor set selection. - Roman Garnett; Michael A. Osborne; Stephen J. Roberts (IPSN, 2010)

Sequential Bayesian Prediction in the Presence of Changepoints and Faults. - Roman Garnett; Michael A. Osborne; Steven Reece; Alex Rogers; Stephen J. Roberts (Comput. J., 2010)

Sequential Dynamic Classification Using Latent Variable Models. - Seung Min Lee; Stephen J. Roberts (Comput. J., 2010)

Sequential non-stationary dynamic classification with sparse feedback. - D. R. Lowne; Stephen J. Roberts; Roman Garnett (Pattern Recognit., 2010)

The Near Constant Acceleration Gaussian Process Kernel for Tracking. - Steven Reece; Stephen J. Roberts (IEEE Signal Process. Lett., 2010)

Robust Measurement Validation in Target Tracking Using Geometric Structure. - Ji Won Yoon; Stephen J. Roberts (IEEE Signal Process. Lett., 2010)

Determining intent using hard/soft data and Gaussian process classifiers. - Steven Reece; Stephen J. Roberts; David Nicholson; Chris M. Lloyd (FUSION, 2011)

Graph marginalization for rapid assignment in wide-area surveillance. - Mark Ebden; Stephen J. Roberts (Ad Hoc Networks, 2011)

Bayesian inference for an adaptive Ordered Probit model: An application to Brain Computer Interfacing. - Ji Won Yoon; Stephen J. Roberts; Matthew Dyson; John Q. Gan (Neural Networks, 2011)

Towards Optimization-Based Multi-Agent Collision-Avoidance Under Continuous Stochastic Dynamics. - Jan-Peter Calliess; Michael Alan Osborne; Stephen J. Roberts (MAPF@AAAI, 2012)

Online Maritime Abnormality Detection Using Gaussian Processes and Extreme Value Theory. - Mark Smith; Steven Reece; Stephen J. Roberts; Iead Rezek (ICDM, 2012)

Network Analysis on Provenance Graphs from a Crowdsourcing Application. - Mark Ebden; Trung Dong Huynh; Luc Moreau 001; Sarvapali D. Ramchurn; Stephen J. Roberts (IPAW, 2012)

Active Learning of Model Evidence Using Bayesian Quadrature. - Michael A. Osborne; David Duvenaud; Roman Garnett; Carl E. Rasmussen; Stephen J. Roberts; Zoubin Ghahramani (NIPS, 2012)

A tutorial on variational Bayesian inference. - Charles W. Fox; Stephen J. Roberts (Artif. Intell. Rev., 2012)

Bayesian one-mode projection for dynamic bipartite graphs - Ioannis Psorakis; Iead Rezek; Zach Frankel; Stephen J. Roberts (CoRR, 2012)

Bayesian Quadrature for Ratios. - Michael A. Osborne; Roman Garnett; Stephen J. Roberts; Christopher Hart; Suzanne Aigrain; Neale Gibson (AISTATS, 2012)

Real-time information processing of environmental sensor network data using bayesian gaussian processes. - Michael A. Osborne; Stephen J. Roberts; Alex Rogers; Nicholas R. Jennings (ACM Trans. Sens. Networks, 2012)

AgentSwitch: towards smart energy tariff selection. - Sarvapali D. Ramchurn; Michael A. Osborne; Oliver Parson; Talal Rahwan; Sasan Maleki; Steven Reece; Trung Dong Huynh; Muddasser Alam; Joel E. Fischer; Tom Rodden; Luc Moreau 001; Stephen J. Roberts (AAMAS, 2013)

Interpretation of Crowdsourced Activities Using Provenance Network Analysis. - Trung Dong Huynh; Mark Ebden; Matteo Venanzi; Sarvapali D. Ramchurn; Stephen J. Roberts; Luc Moreau 001 (HCOMP, 2013)

Discovering Latent Association Structure via Bayesian one-mode Projection of Temporal Bipartite Graphs. - Ioannis Psorakis; Iead Rezek; Zach Frankel; Stephen J. Roberts (MLDM Posters, 2013)

Multi-Agent Planning with Mixed-Integer Programming and Adaptive Interaction Constraint Generation (Extended Abstract). - Jan-P. Calliess; Stephen J. Roberts (SOCS, 2013)

Stochastic processes and feedback-linearisation for online identification and Bayesian adaptive control of fully-actuated mechanical systems. - Jan-Peter Calliess; Antonis Papachristodoulou; Stephen J. Roberts (CoRR, 2013)

Dynamic Bayesian Combination of Multiple Imperfect Classifiers. - Edwin Simpson; Stephen J. Roberts; Ioannis Psorakis; Arfon M. Smith (Decision Making and Imperfection, 2013)

Conservative collision prediction and avoidance for stochastic trajectories in continuous time and space. - Jan-Peter Calliess; Michael A. Osborne; Stephen J. Roberts (AAMAS, 2014)

AtomicOrchid: human-agent collectives to the rescue. - Sarvapali D. Ramchurn; Feng Wu 001; Wenchao Jiang; Joel E. Fischer; Steven Reece; Chris Greenhalgh; Tom Rodden; Nicholas R. Jennings; Stephen J. Roberts (AAMAS, 2014)

Sampling for Inference in Probabilistic Models with Fast Bayesian Quadrature. - Tom Gunter; Michael A. Osborne; Roman Garnett; Philipp Hennig; Stephen J. Roberts (NIPS, 2014)

Efficient Bayesian Nonparametric Modelling of Structured Point Processes. - Tom Gunter; Chris M. Lloyd; Michael A. Osborne; Stephen J. Roberts (UAI, 2014)

Human-agent collectives. - Nicholas R. Jennings; Luc Moreau 001; David Nicholson; Sarvapali D. Ramchurn; Stephen J. Roberts; Tom Rodden; Alex Rogers (Commun. ACM, 2014)

Communication Communities in MOOCs. - Nabeel Gillani; Rebecca Eynon; Michael A. Osborne; Isis Hjorth; Stephen J. Roberts (CoRR, 2014)

Efficient state-space inference of periodic latent force models. - Steven Reece; Siddhartha Ghosh; Alex Rogers; Stephen J. Roberts; Nicholas R. Jennings (J. Mach. Learn. Res., 2014)

Maritime abnormality detection using Gaussian processes. - Mark Smith; Steven Reece; Stephen J. Roberts; Ioannis Psorakis; Iead Rezek (Knowl. Inf. Syst., 2014)

HAC-ER: A Disaster Response System based on Human-Agent Collectives. - Sarvapali D. Ramchurn; Trung Dong Huynh; Yuki Ikuno; Jack Flann; Feng Wu 001; Luc Moreau 001; Nicholas R. Jennings; Joel E. Fischer; Wenchao Jiang; Tom Rodden; Edwin Simpson; Steven Reece; et al. (AAMAS, 2015)

Variational Inference for Gaussian Process Modulated Poisson Processes. - Chris M. Lloyd; Tom Gunter; Michael A. Osborne; Stephen J. Roberts (ICML, 2015)

Scalable Nonparametric Bayesian Inference on Point Processes with Gaussian Processes. - Yves-Laurent Kom Samo; Stephen J. Roberts (ICML, 2015)

Language Understanding in the Wild: Combining Crowdsourcing and Machine Learning. - Edwin Simpson; Matteo Venanzi; Steven Reece; Pushmeet Kohli; John Guiver; Stephen J. Roberts; Nicholas R. Jennings (WWW, 2015)

A Sparse Gaussian Process Framework for Photometric Redshift Estimation. - Ibrahim A. Almosallam 001; Sam N. Lindsay; Matt J. Jarvis; Stephen J. Roberts (CoRR, 2015)

Detecting bird sound in unknown acoustic background using crowdsourced training data. - Timos Papadopoulos; Stephen J. Roberts; Kathy Willis (CoRR, 2015)

Modeling the Thermal Dynamics of Buildings: A Latent-Force- Model-Based Approach. - Siddhartha Ghosh; Steven Reece; Alex Rogers; Stephen J. Roberts; Areej Malibari; Nicholas R. Jennings (ACM Trans. Intell. Syst. Technol., 2015)

Bayesian Methods for Intelligent Task Assignment in Crowdsourcing Systems. - Edwin Simpson; Stephen J. Roberts (Decision Making, 2015)

Latent Point Process Allocation. - Chris M. Lloyd; Tom Gunter; Michael A. Osborne; Stephen J. Roberts; Tom Nickson (AISTATS, 2016)

Bayesian Gaussian processes for identifying the deteriorating patient. - Glen Wright Colopy; Marco A. F. Pimentel; Stephen J. Roberts; David A. Clifton (EMBC, 2016)

Human-agent collaboration for disaster response. - Sarvapali D. Ramchurn; Feng Wu 001; Wenchao Jiang; Joel E. Fischer; Steven Reece; Stephen J. Roberts; Tom Rodden; Chris Greenhalgh; Nicholas R. Jennings (Auton. Agents Multi Agent Syst., 2016)

A Disaster Response System based on Human-Agent Collectives. - Sarvapali D. Ramchurn; Trung Dong Huynh; Feng Wu 001; Yuki Ikuno; Jack Flann; Luc Moreau 001; Joel E. Fischer; Wenchao Jiang; Tom Rodden; Edwin Simpson; Steven Reece; Stephen J. Roberts; et al. (J. Artif. Intell. Res., 2016)

String and Membrane Gaussian Processes. - Yves-Laurent Kom Samo; Stephen J. Roberts (J. Mach. Learn. Res., 2016)

Identifying Sources of Discrimination Risk in the Life Cycle of Machine Intelligence Applications under New European Union Regulations. - Syed Ali Asad Rizvi; Elmarie van Heerden; Arnold Salas; Favour Nyikosa; Stephen J. Roberts; Michael A. Osborne; Elmer Rodriguez (AAAI Spring Symposia, 2017)

Distribution of Gaussian Process Arc Lengths. - Justin Bewsher; Alessandra Tosi; Michael A. Osborne; Stephen J. Roberts (AISTATS, 2017)

Bayesian optimisation of Gaussian processes for identifying the deteriorating patient. - Glen Wright Colopy; Marco A. F. Pimentel; Stephen J. Roberts; David A. Clifton (BHI, 2017)

Entropic determinants of massive matrices. - Diego Granziol; Stephen J. Roberts (IEEE BigData, 2017)

Likelihood-based artefact detection in continuously-acquired patient vital signs. - Glen Wright Colopy; Tingting Zhu 001; Lei A. Clifton; Stephen J. Roberts; David A. Clifton (EMBC, 2017)

Entropic Trace Estimates for Log Determinants. - Jack K. Fitzsimons; Diego Granziol; Kurt Cutajar; Michael A. Osborne; Maurizio Filippone; Stephen J. Roberts (ECML/PKDD (1), 2017)

Optimal Client Recommendation for Market Makers in Illiquid Financial Products. - Dieter Hendricks; Stephen J. Roberts (ECML/PKDD (3), 2017)

Bayesian Heatmaps: Probabilistic Classification with Multiple Unreliable Information Sources. - Edwin Simpson; Steven Reece; Stephen J. Roberts (ECML/PKDD (2), 2017)

Bayesian Inference of Log Determinants. - Jack K. Fitzsimons; Kurt Cutajar; Maurizio Filippone; Michael A. Osborne; Stephen J. Roberts (UAI, 2017)

Mosquito Detection with Neural Networks: The Buzz of Deep Learning. - Ivan Kiskin; Bernardo Pérez Orozco; Theo Windebank; Davide Zilli; Marianne Sinka; Kathy Willis; Stephen J. Roberts (CoRR, 2017)

A Novel Approach to Forecasting Financial Volatility with Gaussian Process Envelopes. - Syed Ali Asad Rizvi; Stephen J. Roberts; Michael A. Osborne; Favour Nyikosa (CoRR, 2017)

Learning from lions: inferring the utility of agents from their trajectories. - Adam D. Cobb; Andrew Markham; Stephen J. Roberts (CoRR, 2017)

Mosquito detection with low-cost smartphones: data acquisition for malaria research. - Yunpeng Li 001; Davide Zilli; Henry C. B. Chan; Ivan Kiskin; Marianne Sinka; Stephen J. Roberts; Kathy Willis (CoRR, 2017)

Cost-sensitive detection with variational autoencoders for environmental acoustic sensing. - Yunpeng Li 001; Ivan Kiskin; Davide Zilli; Marianne Sinka; Henry C. B. Chan; Kathy Willis; Stephen J. Roberts (CoRR, 2017)

Safe Policy Search with Gaussian Process Models. - Kyriakos Polymenakos; Alessandro Abate; Stephen J. Roberts (CoRR, 2017)

Novel Exploration Techniques (NETs) for Malaria Policy Interventions. - Oliver Bent; Sekou L. Remy; Stephen J. Roberts; Aisha Walcott-Bryant (AAAI, 2018)

Learning Against Non-Stationary Agents with Opponent Modelling and Deep Reinforcement Learning. - Richard Everett 001; Stephen J. Roberts (AAAI Spring Symposia, 2018)

Bayesian Nonparametrics and Feedback-Linearisation of Discretised Control-Affine Systems. - Jan-Peter Calliess; Antonis Papachristodoulou; Stephen J. Roberts (CDC, 2018)

Fast mosquito acoustic detection with field cup recordings: an initial investigation. - Yunpeng Li 001; Ivan Kiskin; Marianne Sinka; Davide Zilli; Henry Chan; Eva Herreros-Moya; Theeraphap Chareonviriyaphap; Rungarun Tisgratog; Kathy Willis; Stephen J. Roberts (DCASE, 2018)

Nonlinear Set Membership Regression with Adaptive Hyper-Parameter Estimation for Online Learning and Control. - Jan-Peter Calliess; Stephen J. Roberts; Carl E. Rasmussen; Jan M. Maciejowski (ECC, 2018)

Optimization, Fast and Slow: Optimally Switching between Local and Bayesian Optimization. - Mark McLeod; Stephen J. Roberts; Michael A. Osborne (ICML, 2018)

Identifying Sources and Sinks in the Presence of Multiple Agents with Gaussian Process Vector Calculus. - Adam D. Cobb; Richard Everett 001; Andrew Markham; Stephen J. Roberts (KDD, 2018)

Scalable Bounding of Predictive Uncertainty in Regression Problems with SLAC. - Arno Blaas; Adam D. Cobb; Jan-Peter Calliess; Stephen J. Roberts (SUM, 2018)

Improved Stochastic Trace Estimation using Mutually Unbiased Bases. - Jack K. Fitzsimons; Michael A. Osborne; Stephen J. Roberts; Joseph Francis Fitzsimons (UAI, 2018)

VBALD - Variational Bayesian Approximation of Log Determinants. - Diego Granziol; Edward Wagstaff; Bin Xin Ru; Michael A. Osborne; Stephen J. Roberts (CoRR, 2018)

Gradient descent in Gaussian random fields as a toy model for high-dimensional optimisation in deep learning. - Mariano Chouza; Stephen J. Roberts; Stefan Zohren (CoRR, 2018)

MOrdReD: Memory-based Ordinal Regression Deep Neural Networks for Time Series Forecasting. - Bernardo Pérez Orozco; Gabriele Abbati; Stephen J. Roberts (CoRR, 2018)

Quantum algorithms for training Gaussian Processes. - Zhikuan Zhao; Jack K. Fitzsimons; Michael A. Osborne; Stephen J. Roberts; Joseph F. Fitzsimons (CoRR, 2018)

Entropic Spectral Learning in Large Scale Networks. - Diego Granziol; Bin Xin Ru; Stefan Zohren; Xiaowen Dong 001; Michael A. Osborne; Stephen J. Roberts (CoRR, 2018)

Loss-Calibrated Approximate Inference in Bayesian Neural Networks. - Adam D. Cobb; Stephen J. Roberts; Yarin Gal (CoRR, 2018)

Sequential sampling of Gaussian process latent variable models. - Martin Tegner; Benjamin Bloem-Reddy; Stephen J. Roberts (CoRR, 2018)

Automated bird sound recognition in realistic settings. - Timos Papadopoulos; Stephen J. Roberts; Katherine J. Willis (CoRR, 2018)

Equality Constrained Decision Trees: For the Algorithmic Enforcement of Group Fairness. - Jack K. Fitzsimons; AbdulRahman Al Ali; Michael A. Osborne; Stephen J. Roberts (CoRR, 2018)

Semi-unsupervised Learning of Human Activity using Deep Generative Models. - Matthew Willetts; Aiden R. Doherty; Stephen J. Roberts; Chris C. Holmes (CoRR, 2018)

Practical Bayesian Learning of Neural Networks via Adaptive Subgradient Methods. - Arnold Salas; Stefan Zohren; Stephen J. Roberts (CoRR, 2018)

A Bayesian optimization approach to compute the Nash equilibria of potential games using bandit feedback. - Anup Aprem; Stephen J. Roberts (CoRR, 2018)

Intersectionality: Multiple Group Fairness in Expectation Constraints. - Jack K. Fitzsimons; Michael A. Osborne; Stephen J. Roberts (CoRR, 2018)

BCCNet: Bayesian classifier combination neural network. - Olga Isupova; Yunpeng Li 001; Danil Kuzin; Stephen J. Roberts; Katherine J. Willis; Steven Reece (CoRR, 2018)

Bayesian deep neural networks for low-cost neurophysiological markers of Alzheimer's disease severity. - Wolfgang Fruehwirt; Adam D. Cobb; Martin Mairhofer; Leonard Weydemann; Heinrich Garn; Reinhold Schmidt; Thomas Benke; Peter Dal-Bianco; Gerhard Ransmayr; Markus Waser; Dieter Grossegger; Pengfei Zhang 001; et al. (CoRR, 2018)

Provenance Network Analytics - An approach to data analytics using data provenance. - Trung Dong Huynh; Mark Ebden; Joel E. Fischer; Stephen J. Roberts; Luc Moreau 001 (Data Min. Knowl. Discov., 2018)

Bayesian Optimization of Personalized Models for Patient Vital-Sign Monitoring. - Glen Wright Colopy; Stephen J. Roberts; David A. Clifton (IEEE J. Biomed. Health Informatics, 2018)

Optimising Worlds to Evaluate and Influence Reinforcement Learning Agents. - Richard Everett 001; Adam D. Cobb; Andrew Markham; Stephen J. Roberts (AAMAS, 2019)

Safe Policy Search Using Gaussian Process Models. - Kyriakos Polymenakos; Alessandro Abate; Stephen J. Roberts (AAMAS, 2019)

WiSE-ALE: Wide Sample Estimator for Aggregate Latent Embedding. - Shuyu Lin; Ronald Clark; Robert Birke; Niki Trigoni; Stephen J. Roberts (DGS@ICLR, 2019)

Asynchronous Batch Bayesian Optimisation with Improved Local Penalisation. - Ahsan S. Alvi; Bin Xin Ru; Jan-Peter Calliess; Stephen J. Roberts; Michael A. Osborne (ICML, 2019)

Semi-Unsupervised Learning with Deep Generative Models: Clustering and Classifying using Ultra-Sparse Labels. - Matthew Willetts; Stephen J. Roberts; Christopher C. Holmes (CoRR, 2019)

WiSE-VAE: Wide Sample Estimator VAE. - Shuyu Lin; Ronald Clark; Robert Birke; Niki Trigoni; Stephen J. Roberts (CoRR, 2019)

Enhancing Time Series Momentum Strategies Using Deep Neural Networks. - Bryan Lim; Stefan Zohren; Stephen J. Roberts (CoRR, 2019)

Population-based Global Optimisation Methods for Learning Long-term Dependencies with RNNs. - Bryan Lim; Stefan Zohren; Stephen J. Roberts (CoRR, 2019)

Robustness Quantification for Classification with Gaussian Processes. - Arno Blaas; Luca Laurenti; Andrea Patane; Luca Cardelli; Marta Kwiatkowska; Stephen J. Roberts (CoRR, 2019)

Disentangling Improves VAEs' Robustness to Adversarial Attacks. - Matthew Willetts; Alexander Camuto; Stephen J. Roberts; Chris C. Holmes (CoRR, 2019)

Adaptive Configuration Oracle for Online Portfolio Selection Methods. - Favour M. Nyikosa; Michael A. Osborne; Stephen J. Roberts (CoRR, 2019)

Balancing Reconstruction Quality and Regularisation in ELBO for VAEs. - Shuyu Lin; Stephen J. Roberts; Niki Trigoni; Ronald Clark (CoRR, 2019)

Disentangling to Cluster: Gaussian Mixture Variational Ladder Autoencoders. - Matthew Willetts; Stephen J. Roberts; Chris C. Holmes (CoRR, 2019)

Regularising Deep Networks with DGMs. - Matthew Willetts; Alexander Camuto; Stephen J. Roberts; Chris C. Holmes (CoRR, 2019)

Introducing an Explicit Symplectic Integration Scheme for Riemannian Manifold Hamiltonian Monte Carlo. - Adam D. Cobb; Atilim Günes Baydin; Andrew Markham; Stephen J. Roberts (CoRR, 2019)

Deep Reinforcement Learning for Trading. - Zihao Zhang; Stefan Zohren; Stephen J. Roberts (CoRR, 2019)

Safety Guarantees for Planning Based on Iterative Gaussian Processes. - Kyriakos Polymenakos; Luca Laurenti; Andrea Patane; Jan-Peter Calliess; Luca Cardelli; Marta Kwiatkowska; Alessandro Abate; Stephen J. Roberts (CoRR, 2019)

Implicit Priors for Knowledge Sharing in Bayesian Neural Networks. - Jack K. Fitzsimons; Sebastian M. Schmon; Stephen J. Roberts (CoRR, 2019)

Indian Buffet Neural Networks for Continual Learning. - Samuel Kessler; Vu Nguyen; Stefan Zohren; Stephen Roberts 001 (CoRR, 2019)

A Maximum Entropy approach to Massive Graph Spectra. - Diego Granziol; Robin Ru; Stefan Zohren; Xiaowen Dong 001; Michael A. Osborne; Stephen J. Roberts (CoRR, 2019)

MLRG Deep Curvature. - Diego Granziol; Xingchen Wan; Timur Garipov; Dmitry P. Vetrov; Stephen Roberts 001 (CoRR, 2019)

A General Framework for Fair Regression. - Jack K. Fitzsimons; AbdulRahman Al Ali; Michael A. Osborne; Stephen J. Roberts (Entropy, 2019)

MEMe: An Accurate Maximum Entropy Method for Efficient Approximations in Large-Scale Machine Learning. - Diego Granziol; Bin Xin Ru; Stefan Zohren; Xiaowen Dong 001; Michael A. Osborne; Stephen J. Roberts (Entropy, 2019)

Gaussian Processes for Personalized Interpretable Volatility Metrics in the Step-Down Ward. - Glen Wright Colopy; Stephen J. Roberts; David A. Clifton (IEEE J. Biomed. Health Informatics, 2019)

DeepLOB: Deep Convolutional Neural Networks for Limit Order Books. - Zihao Zhang; Stefan Zohren; Stephen J. Roberts (IEEE Trans. Signal Process., 2019)

Adversarial Robustness Guarantees for Classification with Gaussian Processes. - Arno Blaas; Andrea Patane; Luca Laurenti; Luca Cardelli; Marta Kwiatkowska; Stephen J. Roberts (AISTATS, 2020)

Semi-Unsupervised Learning: Clustering and Classifying using Ultra-Sparse Labels. - Matthew Willetts; Stephen J. Roberts; Chris C. Holmes (IEEE BigData, 2020)

Safety Guarantees for Iterative Predictions with Gaussian Processes. - Kyriakos Polymenakos; Luca Laurenti; Andrea Patane; Jan-Peter Calliess; Luca Cardelli; Marta Kwiatkowska; Alessandro Abate; Stephen J. Roberts (CDC, 2020)

Zero-shot and few-shot time series forecasting with ordinal regression recurrent neural networks. - Bernardo Pérez Orozco; Stephen J. Roberts (ESANN, 2020)

An Overview of Gaussian process Regression for Volatility Forecasting. - Bingqing Liu; Ivan Kiskin; Stephen Roberts 001 (ICAIIC, 2020)

Humbug Zooniverse: A Crowd-Sourced Acoustic Mosquito Dataset. - Ivan Kiskin; Adam D. Cobb; Lawrence Wang; Stephen Roberts 001 (ICASSP, 2020)

Anomaly Detection for Time Series Using VAE-LSTM Hybrid Model. - Shuyu Lin; Ronald Clark; Robert Birke; Sandro Schönborn; Niki Trigoni; Stephen J. Roberts (ICASSP, 2020)

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

Bayesian Optimisation over Multiple Continuous and Categorical Inputs. - Bin Xin Ru; Ahsan S. Alvi; Vu Nguyen; Michael A. Osborne; Stephen J. Roberts (ICML, 2020)

Recurrent Neural Filters: Learning Independent Bayesian Filtering Steps for Time Series Prediction. - Bryan Lim; Stefan Zohren; Stephen Roberts 001 (IJCNN, 2020)

Explicit Regularisation in Gaussian Noise Injections. - Alexander Camuto; Matthew Willetts; Umut Simsekli; Stephen J. Roberts; Chris C. Holmes (NeurIPS, 2020)

Provably Efficient Online Hyperparameter Optimization with Population-Based Bandits. - Jack Parker-Holder; Vu Nguyen; Stephen J. Roberts (NeurIPS, 2020)

Effective Diversity in Population Based Reinforcement Learning. - Jack Parker-Holder; Aldo Pacchiano; Krzysztof Marcin Choromanski; Stephen J. Roberts (NeurIPS, 2020)

SafePILCO: A Software Tool for Safe and Data-Efficient Policy Synthesis. - Kyriakos Polymenakos; Nikitas Rontsis; Alessandro Abate; Stephen J. Roberts (QEST, 2020)

Portfolio optimization for cointelated pairs: SDEs vs Machine learning. - Babak Mahdavi-Damghani; Konul Mustafayeva; Cristin Buescu; Stephen Roberts 001 (Algorithmic Finance, 2020)

Lazily Adapted Constant Kinky Inference for nonparametric regression and model-reference adaptive control. - Jan-Peter Calliess; Stephen J. Roberts; Carl Edward Rasmussen; Jan M. Maciejowski (Autom., 2020)

Detecting Changes in Asset Co-Movement Using the Autoencoder Reconstruction Ratio. - Bryan Lim; Stefan Zohren; Stephen Roberts 001 (CoRR, 2020)

One-Shot Bayes Opt with Probabilistic Population Based Training. - Jack Parker-Holder; Vu Nguyen; Stephen Roberts 001 (CoRR, 2020)

Iterate Averaging Helps: An Alternative Perspective in Deep Learning. - Diego Granziol; Xingchen Wan; Stephen Roberts 001 (CoRR, 2020)

Mixture Density Conditional Generative Adversarial Network Models (MD-CGAN). - Jaleh Zand; Stephen Roberts 001 (CoRR, 2020)

VIGN: Variational Integrator Graph Networks. - Shaan Desai; Stephen Roberts 001 (CoRR, 2020)

Deep Learning for Portfolio Optimisation. - Zihao Zhang; Stefan Zohren; Stephen Roberts 001 (CoRR, 2020)

On Optimism in Model-Based Reinforcement Learning. - Aldo Pacchiano; Philip J. Ball; Jack Parker-Holder; Krzysztof Choromanski; Stephen Roberts 001 (CoRR, 2020)

Relaxed-Responsibility Hierarchical Discrete VAEs. - Matthew Willetts; Xenia Miscouridou; Stephen J. Roberts; Chris C. Holmes (CoRR, 2020)

Explaining the Adaptive Generalisation Gap. - Diego Granziol; Samuel Albanie; Xingchen Wan; Stephen J. Roberts (CoRR, 2020)

Building Cross-Sectional Systematic Strategies By Learning to Rank. - Daniel Poh; Bryan Lim; Stefan Zohren; Stephen J. Roberts (CoRR, 2020)

Thresholded ConvNet ensembles: neural networks for technical forecasting. - Sid Ghoshal; Stephen Roberts 001 (Neural Comput. Appl., 2020)

Bioacoustic detection with wavelet-conditioned convolutional neural networks. - Ivan Kiskin; Davide Zilli; Yunpeng Li 001; Marianne Sinka; Kathy Willis; Stephen J. Roberts (Neural Comput. Appl., 2020)

Learning Bijective Feature Maps for Linear ICA. - Alexander Camuto; Matthew Willetts; Chris C. Holmes; Brooks Paige; Stephen J. Roberts (AISTATS, 2021)

Towards a Theoretical Understanding of the Robustness of Variational Autoencoders. - Alexander Camuto; Matthew Willetts; Stephen J. Roberts; Chris C. Holmes; Tom Rainforth (AISTATS, 2021)

Improving VAEs' Robustness to Adversarial Attack. - Matthew Willetts; Alexander Camuto; Tom Rainforth; Stephen J. Roberts; Christopher C. Holmes (ICLR, 2021)

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

HumBugDB: A Large-scale Acoustic Mosquito Dataset. - Ivan Kiskin; Marianne Sinka; Adam D. Cobb; Waqas Rafique; Lawrence Wang; Davide Zilli; Benjamin Gutteridge; Rinita Dam; Theodoros Marinos; Yunpeng Li 001; Dickson Msaky; Emmanuel Kaindoa; et al. (NeurIPS Datasets and Benchmarks, 2021)

Tuning Mixed Input Hyperparameters on the Fly for Efficient Population Based AutoRL. - Jack Parker-Holder; Vu Nguyen; Shaan Desai; Stephen J. Roberts (NeurIPS, 2021)

Automatic Acoustic Mosquito Tagging with Bayesian Neural Networks. - Ivan Kiskin; Adam D. Cobb; Marianne Sinka; Kathy Willis; Stephen J. Roberts (ECML/PKDD (4), 2021)

Hierarchical Indian buffet neural networks for Bayesian continual learning. - Samuel Kessler; Vu Nguyen; Stefan Zohren; Stephen J. Roberts (UAI, 2021)

Towards tractable optimism in model-based reinforcement learning. - Aldo Pacchiano; Philip J. Ball; Jack Parker-Holder; Krzysztof Choromanski; Stephen Roberts 001 (UAI, 2021)

A Bayesian Optimization Approach to Compute Nash Equilibrium of Potential Games Using Bandit Feedback. - Anup Aprem; Stephen Roberts 001 (Comput. J., 2021)

The Effect of Prior Lipschitz Continuity on the Adversarial Robustness of Bayesian Neural Networks. - Arno Blaas; Stephen J. Roberts (CoRR, 2021)

OffCon3: What is state of the art anyway? - Philip J. Ball; Stephen J. Roberts (CoRR, 2021)

Enhancing Cross-Sectional Currency Strategies by Ranking Refinement with Transformer-based Architectures. - Daniel Poh; Bryan Lim; Stefan Zohren; Stephen J. Roberts (CoRR, 2021)

Slow Momentum with Fast Reversion: A Trading Strategy Using Deep Learning and Changepoint Detection. - Kieran Wood; Stephen J. Roberts; Stefan Zohren (CoRR, 2021)

Can convolutional ResNets approximately preserve input distances? A frequency analysis perspective. - Lewis Smith; Joost van Amersfoort; Haiwen Huang; Stephen J. Roberts; Yarin Gal (CoRR, 2021)

Port-Hamiltonian Neural Networks for Learning Explicit Time-Dependent Dynamical Systems. - Shaan Desai; Marios Mattheakis; David Sondak; Pavlos Protopapas; Stephen J. Roberts (CoRR, 2021)

Revisiting Design Choices in Model-Based Offline Reinforcement Learning. - Cong Lu; Philip J. Ball; Jack Parker-Holder; Michael A. Osborne; Stephen J. Roberts (CoRR, 2021)

One-Shot Transfer Learning of Physics-Informed Neural Networks. - Shaan Desai; Marios Mattheakis; Hayden Joy; Pavlos Protopapas; Stephen J. Roberts (CoRR, 2021)

Trading with the Momentum Transformer: An Intelligent and Interpretable Architecture. - Kieran Wood; Sven Giegerich; Stephen J. Roberts; Stefan Zohren (CoRR, 2021)

Optimal pricing in black box producer-consumer Stackelberg games using revealed preference feedback. - Anup Aprem; Stephen J. Roberts (Neurocomputing, 2021)

Same State, Different Task: Continual Reinforcement Learning without Interference. - Samuel Kessler; Jack Parker-Holder; Philip J. Ball; Stefan Zohren; Stephen J. Roberts (AAAI, 2022)

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

On-the-fly Strategy Adaptation for ad-hoc Agent Coordination. - Jaleh Zand; Jack Parker-Holder; Stephen J. Roberts (AAMAS, 2022)

Uncertainty Estimation with a VAE-Classifier Hybrid Model. - Shuyu Lin; Ronald Clark; Niki Trigoni; Stephen J. Roberts (ICASSP, 2022)

Robust and Scalable SDE Learning: A Functional Perspective. - Scott Alexander Cameron; Tyron Luke Cameron; Arnu Pretorius; Stephen J. Roberts (ICLR, 2022)

Revisiting Design Choices in Offline Model Based Reinforcement Learning. - Cong Lu; Philip J. Ball; Jack Parker-Holder; Michael A. Osborne; Stephen J. Roberts (ICLR, 2022)

Stabilizing Off-Policy Deep Reinforcement Learning from Pixels. - Edoardo Cetin; Philip J. Ball; Stephen J. Roberts; Oya Çeliktutan (ICML, 2022)

The ACM Multimedia 2022 Computational Paralinguistics Challenge: Vocalisations, Stuttering, Activity, & Mosquitoes. - 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; et al. (ACM Multimedia, 2022)

Learning General World Models in a Handful of Reward-Free Deployments. - Yingchen Xu; Jack Parker-Holder; Aldo Pacchiano; Philip J. Ball; Oleh Rybkin; Stephen Roberts 001; Tim Rocktäschel; Edward Grefenstette (NeurIPS, 2022)

Maximum Entropy Approach to Massive Graph Spectrum Learning with Applications. - Diego Granziol; Binxin Ru; Xiaowen Dong 001; Stefan Zohren; Michael A. Osborne; Stephen J. Roberts (Algorithms, 2022)

Transfer Ranking in Finance: Applications to Cross-Sectional Momentum with Data Scarcity. - Daniel Poh; Stephen J. Roberts; Stefan Zohren (CoRR, 2022)

The Surprising Effectiveness of Latent World Models for Continual Reinforcement Learning. - Samuel Kessler; Piotr Milos; Jack Parker-Holder; Stephen J. Roberts (CoRR, 2022)

A large-scale and PCR-referenced vocal audio dataset for COVID-19. - 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; et al. (CoRR, 2022)

Audio-based AI classifiers show no evidence of improved COVID-19 screening over simple symptoms checkers. - 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; et al. (CoRR, 2022)

Statistical Design and Analysis for Robust Machine Learning: A Case Study from COVID-19. - Davide Pigoli; Kieran Baker; Jobie Budd; Lorraine Butler; Harry Coppock; Sabrina Egglestone; Steven G. Gilmour; Chris C. Holmes; David Hurley; Radka Jersakova; Ivan Kiskin; Vasiliki Koutra; et al. (CoRR, 2022)

Learning Rates as a Function of Batch Size: A Random Matrix Theory Approach to Neural Network Training. - Diego Granziol; Stefan Zohren; Stephen Roberts 001 (J. Mach. Learn. Res., 2022)

Adversarial Robustness Guarantees for Gaussian Processes. - Andrea Patane; Arno Blaas; Luca Laurenti; Luca Cardelli; Stephen Roberts 001; Marta Kwiatkowska (J. Mach. Learn. Res., 2022)

The Effectiveness of World Models for Continual Reinforcement Learning. - Samuel Kessler; Mateusz Ostaszewski; Michal Pawel Bortkiewicz; Mateusz Zarski; Maciej Wolczyk; Jack Parker-Holder; Stephen J. Roberts; Piotr Milos (CoLLAs, 2023)

Nonparametric Boundary Geometry in Physics Informed Deep Learning. - Scott Alexander Cameron; Arnu Pretorius; Stephen J. Roberts (NeurIPS, 2023)

Guidelines for building a realistic algorithmic trading market simulator for backtesting while incorporating market impact: Agent-Based Strategies in Neural Network Format, Ecosystem Dynamics & Detection. - Babak Mahdavi-Damghani; Stephen Roberts 001 (Algorithmic Finance, 2023)

Spatio-Temporal Momentum: Jointly Learning Time-Series and Cross-Sectional Strategies. - Wee Ling Tan; Stephen J. Roberts; Stefan Zohren (CoRR, 2023)

SANE: The phases of gradient descent through Sharpness Adjusted Number of Effective parameters. - Lawrence Wang; Stephen J. Roberts (CoRR, 2023)

The instabilities of large learning rate training: a loss landscape view. - Lawrence Wang; Stephen Roberts 001 (CoRR, 2023)

Network Momentum across Asset Classes. - Xingyue Pu; Stephen J. Roberts; Xiaowen Dong 001; Stefan Zohren (CoRR, 2023)

Learning to Learn Financial Networks for Optimising Momentum Strategies. - Xingyue Pu; Stefan Zohren; Stephen J. Roberts; Xiaowen Dong 001 (CoRR, 2023)

Few-Shot Learning Patterns in Financial Time-Series for Trend-Following Strategies. - Kieran Wood; Samuel Kessler; Stephen J. Roberts; Stefan Zohren (CoRR, 2023)

On the Sample Complexity of Lipschitz Constant Estimation. - Julien Walden Huang; Stephen J. Roberts; Jan-Peter Calliess (Trans. Mach. Learn. Res., 2023)

On Sequential Bayesian Inference for Continual Learning. - Samuel Kessler; Adam D. Cobb; Tim G. J. Rudner; Stefan Zohren; Stephen J. Roberts (Entropy, 2023)

Deep Learning for Options Trading: An End-To-End Approach. - Wee Ling Tan; Stephen Roberts 001; Stefan Zohren (ICAIF, 2024)

Can Stability be Detrimental? Better Generalization through Gradient Descent Instabilities. - Lawrence Wang; Stephen J. Roberts (CoRR, 2024)

Iterate Averaging in the Quest for Best Test Error. - Diego Granziol; Nicholas P. Baskerville; Xingchen Wan; Samuel Albanie; Stephen Roberts 001 (J. Mach. Learn. Res., 2024)

Audio-based AI classifiers show no evidence of improved COVID-19 screening over simple symptoms checkers. - 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; et al. (Nat. Mac. Intell., 2024)

Standardized low-resolution brain electromagnetic tomography does not improve EEG Alzheimer's disease assessment. - Wolfgang Fruehwirt; Martin Mairhofer; Andreas Hahn 001; Heinrich Garn; Markus Waser; Reinhold Schmidt; Thomas Benke; Peter Dal-Bianco; Gerhard Ransmayr; Dieter Grossegger; Stephen J. Roberts; Georg Dorffner (NeuroImage, 2025)

Beyond Accuracy: EcoL2 Metric for Sustainable Neural PDE Solvers. - Taniya Kapoor; Abhishek Chandra; Anastasios Stamou; Stephen J. Roberts (CoRR, 2025)

Prediction-Oriented Subsampling from Data Streams. - Benedetta Lavinia Mussati; Freddie Bickford Smith; Tom Rainforth; Stephen Roberts 001 (CoRR, 2025)