Stephen J. Roberts

Charles W. Fox, Stephen J. Roberts: A tutorial on variational Bayesian inference. Artif. Intell. Rev. 38(2): 85-95 (2012)

Michael A. Osborne, Roman Garnett, Stephen J. Roberts, Christopher Hart, Suzanne Aigrain, Neale Gibson: Bayesian Quadrature for Ratios. Journal of Machine Learning Research - Proceedings Track 22: 832-840 (2012)

Michael A. Osborne, Stephen J. Roberts, Alex Rogers, Nicholas R. Jennings: Real-time information processing of environmental sensor network data using bayesian gaussian processes. TOSN 9(1): 1 (2012)

Mark Smith, Steven Reece, Stephen J. Roberts, Iead Rezek: Online Maritime Abnormality Detection Using Gaussian Processes and Extreme Value Theory. ICDM 2012: 645-654

Michael A. Osborne, David K. Duvenaud, Roman Garnett, Carl E. Rasmussen, Stephen J. Roberts, Zoubin Ghahramani: Active Learning of Model Evidence Using Bayesian Quadrature. NIPS 2012: 46-54

Ioannis Psorakis, Iead Rezek, Zach Frankel, Stephen J. Roberts: Bayesian one-mode projection for dynamic bipartite graphs. CoRR abs/1212.2767 (2012)

Ji Won Yoon, Stephen J. Roberts, Matthew Dyson, John Q. Gan: Bayesian inference for an adaptive Ordered Probit model: An application to Brain Computer Interfacing. Neural Networks 24(7): 726-734 (2011)

Seung Min Lee, Stephen J. Roberts: Sequential Dynamic Classification Using Latent Variable Models. Comput. J. 53(9): 1415-1429 (2010)

Roman Garnett, Michael A. Osborne, Steven Reece, Alex Rogers, Stephen J. Roberts: Sequential Bayesian Prediction in the Presence of Changepoints and Faults. Comput. J. 53(9): 1430-1446 (2010)

D. R. Lowne, Stephen J. Roberts, Roman Garnett: Sequential non-stationary dynamic classification with sparse feedback. Pattern Recognition 43(3): 897-905 (2010)

Michael A. Osborne, Roman Garnett, Stephen J. Roberts: Active Data Selection for Sensor Networks with Faults and Changepoints. AINA 2010: 533-540

Roman Garnett, Michael A. Osborne, Stephen J. Roberts: Bayesian optimization for sensor set selection. IPSN 2010: 209-219

Lyndsey C. Pickup, David P. Capel, Stephen J. Roberts, Andrew Zisserman: Bayesian Methods for Image Super-Resolution. Comput. J. 52(1): 101-113 (2009)

Chun Sing Louis Tsui, John Q. Gan, Stephen J. Roberts: 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. Med. Biol. Engineering and Computing 47(3): 257-265 (2009)

Ji Won Yoon, Stephen J. Roberts, Matthew Dyson, John Q. Gan: Adaptive classification for Brain Computer Interface systems using Sequential Monte Carlo sampling. Neural Networks 22(9): 1286-1294 (2009)

Roman Garnett, Michael A. Osborne, Stephen J. Roberts: Sequential Bayesian prediction in the presence of changepoints. ICML 2009: 44

Iead Rezek, David S. Leslie, Steven Reece, Stephen J. Roberts, Alex Rogers, Rajdeep K. Dash, Nicholas R. Jennings: On Similarities between Inference in Game Theory and Machine Learning. J. Artif. Intell. Res. (JAIR) 33: 259-283 (2008)

Hyoungjoo Lee, Stephen J. Roberts: On-line novelty detection using the Kalman filter and extreme value theory. ICPR 2008: 1-4

Ji Won Yoon, Stephen J. Roberts, Matthew Dyson, John Q. Gan: Adaptive Classification by Hybrid EKF with Truncated Filtering: Brain Computer Interfacing. IDEAL 2008: 370-377

Michael A. Osborne, Stephen J. Roberts, Alex Rogers, Sarvapali D. Ramchurn, Nicholas R. Jennings: Towards Real-Time Information Processing of Sensor Network Data Using Computationally Efficient Multi-output Gaussian Processes. IPSN 2008: 109-120

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

Lyndsey C. Pickup, Stephen J. Roberts, Andrew Zisserman: Optimizing and Learning for Super-resolution. BMVC 2006: 439-448

Lyndsey C. Pickup, David P. Capel, Stephen J. Roberts, Andrew Zisserman: Bayesian Image Super-resolution, Continued. NIPS 2006: 1089-1096

Sach Mukherjee, Stephen J. Roberts: A Theoretical Analysis of the Selection of Differentially Expressed Genes. J. Bioinformatics and Computational Biology 3(3): 627-644 (2005)

Sach Mukherjee, Stephen J. Roberts, Mark J. van der Laan: Data-adaptive test statistics for microarray data. ECCB/JBI 2005: 114

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

Peter Sykacek, Stephen J. Roberts, Maria Stokes: Adaptive BCI based on variational Bayesian Kalman filtering: an empirical evaluation. IEEE Trans. Biomed. Engineering 51(5): 719-727 (2004)

Sach Mukherjee, Stephen J. Roberts: A Theoretical Analysis of Gene Selection. CSB 2004: 131-141

Sach Mukherjee, Stephen J. Roberts: Probabilistic Consistency Analysis for Gene Selection. CSB 2004: 487-488

S. N. Mukherjee, Stephen J. Roberts, Peter Sykacek, Sarah J. Gurr: Gene ranking using bootstrapped P-values. SIGKDD Explorations 5(2): 16-22 (2003)

Nicholas P. Hughes, Lionel Tarassenko, Stephen J. Roberts: Markov Models for Automated ECG Interval Analysis. NIPS 2003

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

Jens Rittscher, Andrew Blake, Stephen J. Roberts: Towards the automatic analysis of complex human body motions. Image Vision Comput. 20(12): 905-916 (2002)

Stephen J. Roberts, Will D. Penny: Variational Bayes for generalized autoregressive models. IEEE Transactions on Signal Processing 50(9): 2245-2257 (2002)

Iead Rezek, Michael Gibbs, Stephen J. Roberts: Maximum a Posteriori Estimation of Coupled Hidden Markov Models. VLSI Signal Processing 32(1-2): 55-66 (2002)

Peter Sykacek, Stephen J. Roberts: Adaptive Classification by Variational Kalman Filtering. NIPS 2002: 737-744

Stephen J. Roberts, Christopher Holmes, Dave Denison: Minimum-Entropy Data Partitioning Using Reversible Jump Markov Chain Monte Carlo. IEEE Trans. Pattern Anal. Mach. Intell. 23(8): 909-914 (2001)

Stephen J. Roberts, Christopher Holmes, Dave Denison: Minimum-Entropy Data Clustering Using Reversible Jump Markov Chain Monte Carlo. ICANN 2001: 103-110

Stephen J. Roberts, William D. Penny: Mixtures of Independent Component Analysers. ICANN 2001: 527-534

Peter Sykacek, Stephen J. Roberts, Iead Rezek, Arthur Flexer, Georg Dorffner: A Probabilistic Approach to High-Resolution Sleep Analysis. ICANN 2001: 617-624

Peter Sykacek, Stephen J. Roberts: Bayesian time series classification. NIPS 2001: 937-944

Stephen J. Roberts, Richard M. Everson, Iead Rezek: Maximum certainty data partitioning. Pattern Recognition 33(5): 833-839 (2000)

Richard M. Everson, Stephen J. Roberts: Independent Component Analysis: A Flexible Nonlinearity and Decorrelating Manifold Approach. Neural Computation 11(8): 1957-1983 (1999)

Dirk Husmeier, William D. Penny, Stephen J. Roberts: An empirical evaluation of Bayesian sampling with hybrid Monte Carlo for training neural network classifiers. Neural Networks 12(4-5): 677-705 (1999)

William D. Penny, Stephen J. Roberts: Bayesian neural networks for classification: how useful is the evidence framework? Neural Networks 12(6): 877-892 (1999)

Stephen J. Roberts, Dirk Husmeier, Iead Rezek, William D. Penny: Bayesian Approaches to Gaussian Mixture Modeling. IEEE Trans. Pattern Anal. Mach. Intell. 20(11): 1133-1142 (1998)

Stephen J. Roberts: Parametric and non-parametric unsupervised cluster analysis. Pattern Recognition 30(2): 261-272 (1997)

Stephen J. Roberts, Lionel Tarassenko: A Probabilistic Resource Allocating Network for Novelty Detection. Neural Computation 6(2): 270-284 (1994)