| 2008 |
| 24 | EE | Hyoung-joo Lee,
Stephen J. Roberts:
On-line novelty detection using the Kalman filter and extreme value theory.
ICPR 2008: 1-4 |
| 23 | EE | 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 |
| 2006 |
| 22 | EE | Lyndsey C. Pickup,
David P. Capel,
Stephen J. Roberts,
Andrew Zisserman:
Bayesian Image Super-resolution, Continued.
NIPS 2006: 1089-1096 |
| 2005 |
| 21 | EE | Sach Mukherjee,
Stephen J. Roberts,
Mark J. van der Laan:
Data-adaptive test statistics for microarray data.
ECCB/JBI 2005: 114 |
| 20 | EE | 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) |
| 2004 |
| 19 | EE | Sach Mukherjee,
Stephen J. Roberts:
A Theoretical Analysis of Gene Selection.
CSB 2004: 131-141 |
| 18 | EE | Sach Mukherjee,
Stephen J. Roberts:
Probabilistic Consistency Analysis for Gene Selection.
CSB 2004: 487-488 |
| 2003 |
| 17 | EE | Lyndsey C. Pickup,
Stephen J. Roberts,
Andrew Zisserman:
A Sampled Texture Prior for Image Super-Resolution.
NIPS 2003 |
| 16 | EE | Nicholas P. Hughes,
Lionel Tarassenko,
Stephen J. Roberts:
Markov Models for Automated ECG Interval Analysis.
NIPS 2003 |
| 15 | EE | S. N. Mukherjee,
Stephen J. Roberts,
Peter Sykacek,
Sarah J. Gurr:
Gene ranking using bootstrapped P-values.
SIGKDD Explorations 5(2): 16-22 (2003) |
| 2002 |
| 14 | EE | Peter Sykacek,
Stephen J. Roberts:
Adaptive Classification by Variational Kalman Filtering.
NIPS 2002: 737-744 |
| 13 | EE | Jens Rittscher,
Andrew Blake,
Stephen J. Roberts:
Towards the automatic analysis of complex human body motions.
Image Vision Comput. 20(12): 905-916 (2002) |
| 12 | EE | 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) |
| 2001 |
| 11 | EE | Stephen J. Roberts,
Christopher Holmes,
Dave Denison:
Minimum-Entropy Data Clustering Using Reversible Jump Markov Chain Monte Carlo.
ICANN 2001: 103-110 |
| 10 | EE | Stephen J. Roberts,
William D. Penny:
Mixtures of Independent Component Analysers.
ICANN 2001: 527-534 |
| 9 | EE | Peter Sykacek,
Stephen J. Roberts,
Iead Rezek,
Arthur Flexer,
Georg Dorffner:
A Probabilistic Approach to High-Resolution Sleep Analysis.
ICANN 2001: 617-624 |
| 8 | EE | Peter Sykacek,
Stephen J. Roberts:
Bayesian time series classification.
NIPS 2001: 937-944 |
| 7 | EE | 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) |
| 2000 |
| 6 | EE | Stephen J. Roberts,
Richard M. Everson,
Iead Rezek:
Maximum certainty data partitioning.
Pattern Recognition 33(5): 833-839 (2000) |
| 1999 |
| 5 | | Richard M. Everson,
Stephen J. Roberts:
Independent Component Analysis: A Flexible Nonlinearity and Decorrelating Manifold Approach.
Neural Computation 11(8): 1957-1983 (1999) |
| 4 | EE | 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) |
| 3 | EE | William D. Penny,
Stephen J. Roberts:
Bayesian neural networks for classification: how useful is the evidence framework?
Neural Networks 12(6): 877-892 (1999) |
| 1998 |
| 2 | EE | 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) |
| 1997 |
| 1 | EE | Stephen J. Roberts:
Parametric and non-parametric unsupervised cluster analysis.
Pattern Recognition 30(2): 261-272 (1997) |