Roberts, Stephen - Department of Engineering Science, University of Oxford

• EXTREME VALUE STATISTICS FOR NOVELTY DETECTION IN BIOMEDICAL DATA PROCESSING
• VARIATIONAL BAYESIAN LEARNING FOR WAVELET INDEPENDENT COMPONENT
• ORIGINAL ARTICLE A self-paced braincomputer interface for controlling a robot
• Overlapping Community Detection using Bayesian Nonnegative Matrix Factorization Ioannis Psorakis,
• A Simple, Quasi-linear, Discrete Model of Vocal Fold Dynamics
• Sequential Forecasting and Decision Making in Dynamic and Incomplete
• Independent Component Analysis: A flexible nonlinearity and decorrelating manifold approach
• PARAMETRIC MODEL ORDER ESTIMATION: A BRIEF REVIEW Iead A. Rezek, Stephen J. Roberts 1
• Combining neural networks with inputdependent weighting factors
• MinimumEntropy Data Partitioning using Reversible Jump Markov Chain Monte Carlo
• Covariancebased weighting for optimal combination of network predictions
• Neural Networks : Friends or Foes? Stephen J. Roberts, Will Penny
• Causal Analysis with Information Flow I.A.Rezek and S.J.Roberts \Lambda
• Realtime BrainComputer Interfacing: a preliminary study using Bayesian learning
• A VALIDATION INDEX FOR ARTIFICIAL NEURAL NETWORKS
• ACOUSTIC EMISSION IN AEROSPACE STRUCTURES W.A. Wright
• COMPUTING EQUILIBRIA FOR TWOPERSON GAMES To appear in: Handbook of Game Theory , Vol. 3, eds. R. J. Aumann and S. Hart, North
• 26+27 Linear Programming 1. The Problem
• Data Decomposition using Independent Component Analysis with Prior Constraints
• Stochastic Complexity Measures for Physiological Signal Analysis I.A.Rezek and S.J.Roberts
• ASSESSING THE CONFIDENCE OF CLASSIFICATION IN ARTIFICIAL NEURAL NETWORKS Stephen J. Roberts 1
• Submitted to Electronics Letters Unsupervised Data Partitioning: a Bayesian Approach
• Decentralized Predictive Sensor Allocation Mark Ebden*, Mark Briers**, and Stephen Roberts*
• Journal of Artificial Intelligence Research 33 (2008) Submitted 12/07; published 10/08 On Similarities between Inference in Game Theory and
• Towards Real-Time Information Processing of Sensor Network Data using Computationally Efficient Multi-output Gaussian Processes
• Variational Methods Bayesian Independent Component Analysis
• Experiments with an EEGbased computer interface
• Markov chain Monte Carlo methods for Bayesian sensor Peter Sykacek (peter@ai.univie.ac.at)
• Adaptive Noise Removal from Complex Signals using the Wavelet Transform
• DETECTION OF SMALL EMBEDDED SIGNALS IN NOISE USING PROBABILISTIC INDEPENDENT COMPONENT ANALYSIS
• Data Projections for the Analysis and Visualisation of Bioinformatics Data
• Probabilistic Consistency Analysis for Gene Selection Sach Mukherjee
• Sequential Dynamic Classification Using Latent Variable Models
• A Review of Parametric Modelling Techniques for EEG Analysis J. Pardey, S. Roberts \Lambda , L. Tarassenko
• An Operator Interpretation of Message Passing Robotics Research Group
• Independent Component Analysis: A flexible nonlinearity and decorrelating manifold approach
• 1 Particle Filters for Non-Stationary ICA Richard Everson 1 and Stephen Roberts 2
• Prediction of feather damage in laying hens using optical flows and
• large variety of algorithms in coding, signal processing, and artificial intelligence may be viewed as instances of
• Unsupervised Clustering using Metric Space Connectedness Iead A. Rezek, Stephen J. Roberts
• Bayesian Multivariate Autoregressive Models with Structured Priors
• Information Geometry Evangelos C. Roussos
• AUTOMATED ASSESSMENT OF VIGILANCE USING COMMITTEES OF RADIAL BASIS FUNCTION ANALYSERS
• Learning Interaction Dynamics with Coupled Hidden Markov Iead Rezek, Peter Sykacek, Stephen J. Roberts
• IEEE TRANSACTIONS ON SIGNAL PROCESSING 1 Perfect sampling for the wavelet
• Submitted to Electronics Letters, December 1996 A Maximum Certainty Approach to Feedforward Neural
• Bayesian time series classification Peter Sykacek
• Haematological and Immunological Data Data set n Input
• A Comparison of Bayesian and Maximum Likelihood Learning of Coupled Hidden Markov Models
• Pigeons combine compass and landmark guidance in familiar route navigation
• Bayes Consistent Classification of EEG Data by Approximate Marginalisation
• Draft 5.3, August 1998: To appear in IEEE Transactions on Pattern Analysis and Machine Learning. Bayesian Approaches to Gaussian Mixture Modelling
• 41. S. Nee, Philos. Tra ns. R. Soc. Lond. B Biol. Sci. 355,
• Computational Mechanism Design for Multi-Sensor Information Fusion
• Robust Cell Nuclei Segmentation Using Statistical Modelling Theodoros Mouroutis Stephen J. Roberts Anil A. Bharath
• NOVELTY, CONFIDENCE & ERRORS IN CONNECTIONIST Stephen J. Roberts & William Penny
• Draft 4.3, March 1998 : Medical & Biological Engineering and Computing Temporal and Spatial Complexity measures for EEGbased Brain
• FLEXIBLE BAYESIAN INDEPENDENT COMPONENT ANALYSIS FOR BLIND SOURCE R.A. Choudrey and S.J. Roberts
• Draft 5.2 February 1999 Novelty Detection using Extreme Value Statistics
• Determining Intent using Hard/Soft Data and Gaussian Process Classifiers
• HIDDEN MARKOV INDEPENDENT COMPONENT ANALYSIS AS A MEASURE OF COUPLING IN MULTIVARIATE FINANCIAL TIME
• Ensemble Hidden Markov Models with Extended Observation Densities for Biosignal Analysis
• THE USE OF ADVANCED INFORMATION PROCESSING METHODS IN EEG ANALYSIS Stephen J. Roberts, Iead A. Rezek, William D. Penny & Richard M. Everson
• Covariancebased weighting for optimal combination of model predictions
• Minimum Entropy Data Partitioning Stephen J. Roberts, Richard Everson & Iead Rezek
• Real-time Brain-Computer Interfacing: a preliminary study using Bayesian learning
• NOVELTY, CONFIDENCE & ERRORS IN CONNECTIONIST SYSTEMS Stephen J. Roberts 1 , William Penny 1 & David Pillot 2
• Envelope Extraction via Complex Homomorphic Filtering I.A.Rezek and S.J.Roberts \Lambda
• Variational Mixture of Bayesian Independent Component Analysers
• DRAFT . . . DRAFT . . . DRAFT . . . DRAFT . . . DRAFT . . . DRAFT Bayesian Image Super-resolution
• BIOINFORMATICS Vol. 00 no. 00 2005
• Probabilistic Consistency Analysis for Gene Selection Sach Mukherjee # and Stephen J. Roberts
• Adaptive BCI based on variational Bayesian Kalman ltering: an empirical evaluation
• Another Look at Conditionally Gaussian Markov Random Fields
• Approximate Inference and Protein-Folding
• Scalespace Unsupervised Cluster Analysis Stephen J. Roberts
• TRACKING ICA FOR EYE-MOVEMENT ARTEFACT REMOVAL Stephen J. Roberts 1 , Richard Everson 2 , Iead Rezek 1 , Peter Anderer 3 & Alois Schlogl 4 .
• From Schrodinger's equation to the quantum search algorithma... Lov K. Groverb)
• Testing the assumptions of linear prediction analysis in normal vowels wF eF vsvia)
• Sequential non-stationary dynamic classification with sparse feedback D.R. Lowne, S.J. Roberts , R. Garnett
• Rumours and Reputation: Evaluating Multi-Dimensional Trust within a Decentralised Reputation System
• Biomechanically Informed Nonlinear Speech Signal
• Adaptive classification by variational Kalman Peter Sykacek
• Plot of the viral load data 0 50 100 150
• AUTOMATED ASSESSMENT OF VIGILANCE USING COMMITTEES OF RADIAL BASIS FUNCTION ANALYSERS
• BLIND SOURCE SEPARATION WITH NON-STATIONARY MIXING USING WAVELETS
• An Introduction to Gaussian Processes for the Kalman Filter Steven Reece and Stephen Roberts
• HIERARCHY, PRIORS AND WAVELETS: STRUCTURE & SIGNAL MODELLING USING ICA
• Soft Partitioning in Networks via Bayesian Non-negative Matrix Factorization
• On-line Novelty Detection Using the Kalman Filter and Extreme Value Theory
• Maximum Certainty Data Partitioning Stephen J. Roberts, Richard Everson & Iead Rezek
• Sequential Bayesian Prediction in the Presence of Changepoints Roman Garnett, Michael A. Osborne, Stephen J. Roberts
• 28 Duality in Linear Programming As we have noted , a linear program is an optimization problem with linear
• USER SPECIFIC TEMPLATE MATCHING FOR EVENT DETECTION USING SINGLE CHANNEL EEG
• EEGbased communication via dynamic neural network models William D. Penny and Stephen J. Roberts
• ESIMTATION OF COUPLED HIDDEN MARKOV MODELS WITH APPLICATION TO BIOSIGNAL
• BAYESIAN ICA WITH HIDDEN MARKOV MODEL SOURCES R.A. Choudrey and S.J. Roberts
• Unsupervised Learning of Ranking Functions for HighDimensional Data
• Regularisation of RBFNetworks with the Bayesian Evidence Scheme
• Bayesian parameter estimation through variational methods Tommi S. Jaakkola Michael I. Jordan
• Engineering Department,
• Multi-Sensor Fault Recovery in the Presence of Known and Unknown Fault Types
• Technical Report PARG-10-01: Sampling for Bayesian Quadrature
• Unifying Learning in Games and Graphical Models I.Rezek, S.J.Roberts
• BAYESIAN INDEPENDENT COMPONENT ANALYSIS WITH PRIOR CONSTRAINTS: AN APPLICATION IN BIOSIGNAL
• Multiscale Voice Morphing Using Radial Basis Function Analysis
• Quantum Computing Functions (QCF) for Matlab Charles Fox
• Correctness of belief propagation in Gaussian graphical models of arbitrary topology
• Notes on Variational Learning W.D. Penny and S.J. Roberts
• Analysis of Avian Robin M. Freeman
• Adaptive Classification by Hybrid EKF with Truncated Filtering
• ARTICLE Communicated by Jean-Pierre Nadal Predictability, Complexity, and Learning
• A Really Friendly Guide to C. Valens, 1999
• NIPS 2002 Vancouver DRAFT Paper Please only refer to final paper Dynamic Structure Super-Resolution
• In Press : Pattern Recognition, April 1996 Parametric and Nonparametric Unsupervised
• EEGBASED ASSESSMENT OF ANAESTHETIC DEPTH USING NEURAL NETWORKS Milos Krkic 1 , Stephen J. Roberts 1 , Iead Rezek 1 & Chris Jordan 2
• VARIATIONAL BAYESIAN MIXTURE OF INDEPENDENT COMPONENT ANALYSERS FOR FINDING SELF-SIMILAR AREAS IN IMAGES
• EEGbased communication: a pattern recognition approach William D. Penny a , Stephen J. Roberts a and Maria J. Stokes b
• NonLinear Kalman Filtering With NonParametric Biscay Distributions
• Variational Bayes for Generalized Autoregressive Models S.J. Roberts 1 & W. D. Penny 2
• Dynamic models for nonstationary signal segmentation
• Noname manuscript No. (will be inserted by the editor)
• I am delighted to introduce the first book on Multimedia Data Mining. When I came to know about this book project undertaken by two of the most active
• Coordination vs. information in multi-agent decision Maike Kaufman and Stephen Roberts
• Sequential Bayesian Decision Making for Multi-Armed R. E. McInerney, S. J. Roberts
• Bayesian Optimization for Sensor Set Selection R. Garnett, M. A. Osborne and S. J. Roberts
• Published by Oxford University Press on behalf of The British Computer Society 2010. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org
• Active Data Selection for Sensor Networks with Faults and Changepoints Michael A. Osborne, Roman Garnett, Stephen J. Roberts
• IEEE SIGNAL PROCESSING LETTERS,MANUSCRIPT 1 Robust Measurement Validation in Target Tracking
• Graph Marginalization for Rapid Assignment in Wide-Area Surveillance
• Multivariate Time Series Forecasting in Incomplete Environments
• Learning from Data Streams with Concept Roman Garnett
• Local Quantum Computing for Fast Probably MAP Inference in Graphical Models
• NONLINEAR, BIOPHYSICALLY-INFORMED SPEECH PATHOLOGY DETECTION Max Little*ab
• Robust, Low-Bandwidth, Multi-Vehicle Mapping Steven Reece and Stephen Roberts
• December 1, 2004 17:46 WSPC/INSTRUCTION FILE jbcbrevised Journal of Bioinformatics and Computational Biology
• Sampling distribution of the SAM statistic Technical Report No. PARG-04-01
• POSITIONAL ENTROPY DURING PIGEON HOMING I: APPLICATION OF BAYESIAN LATENT STATE MODELLING
• Gene Ranking Using Bootstrapped P-values S. N. Mukherjee
• Ensemble Coupled Hidden Markov Models for Joint Characterisation of Dynamic Signals
• ENSEMBLE HIDDEN MARKOV MODELS FOR BIOSIGNAL ANALYSIS Iead Rezek and Stephen J. Roberts
• Towards the automatic analysis of complex human body motions J. Rittschera,*, A. Blakeb
• LEARNING FROM DATA STREAMS WITH CONCEPT DRIFT
• Data-adaptive test statistics gene expression arrays
• Observable operator models for discrete stochastic time series1
• EXTENSIONS OF ICA AS MODELS OF NATURAL IMAGES AND VISUAL PROCESSING
• Charting a manifold Matthew Brand, MERL (draft revised Oct 2002 to appear NIPS'02)
• Gaussian Processes for Prediction Technical Report PARG-07-01
• Voice Morphing Using the Generative Topographic Mapping Christina ORPHANIDOU
• AN ITERATIVE SIGNAL DETECTION ALGORITHM BASED ON BAYESIAN BELIEF PROPAGATION IDEAS
• Bayesian Gaussian Processes for Sequential Prediction,
• MinimumEntropy Data Clustering using Reversible Jump Markov Chain Monte Carlo
• Prediction of Homing Pigeon Flight Paths using Gaussian
• Positional Entropy during Pigeon Homing II: navigational interpretation of Bayesian Latent State Models.
• Local Decision-Making in Multi-Agent Maike Kaufman
• Visualizing uncertainty in reliability functions with application to aero engine overhaul
• A Multi-Dimensional Trust Model for Heterogeneous Contract Observations Steven Reece and Stephen Roberts
• Gaussian Processes for Global Optimization Michael A. Osborne, Roman Garnett, and Stephen J. Roberts
• A Multi-Agent Simulation System for Prediction and Scheduling of Aero Engine Overhaul
• Depth of Anaesthesia Assessment with Generative Polyspectral Models I. Rezek, S. J. Roberts, E. Siva
• EXTREME VALUE STATISTICS FOR NOVELTY DETECTION IN BIOMEDICAL SIGNAL Stephen J. Roberts
• Interval Arithmetic Kalman Filtering Steven Reece
• Draft 3.1 : To appear in IEE Proceedings on Vision, Signal & Image Processing Independent Component Analysis: Source Assessment & Separation,
• Cytokines and HHV (Ifa and Elisa) Data set KS+ (class 1) KS--(class 3)
• Variational Bayesian Independent Component Analysis with Flexible
• 2004-01-1418 Instantaneous Exhaust Temperature Measurements Using
• Blind Source Separation by Sparse Decomposition in a Signal Dictionary
• Confidence Intervals and Prediction Intervals for FeedForward Neural Networks
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• Basic concepts in quantum computation Artur Ekert, Patrick Hayden and Hitoshi Inamori
• Bayesian neural networks for classification: how useful is the evidence framework ?
• LETTER Communicated by Hagai Attias Online Model Selection Based on the Variational Bayes
• A Theoretical Analysis of Gene Selection S. N. Mukherjee
• Journal of Theoretical Biology 239 (2006) 7178 An edge-detection approach to investigating pigeon navigation
• Blind source separation using spatial and temporal priors
• The ALADDIN Project: Intelligent Agents for Disaster Management N.M. Adams1
• LEARNING HIERARCHICAL DYNAMICS USING INDEPENDENT COMPONENT ANALYSIS
• MAXIMUM A POSTERIORI ESTIMATION OF COUPLED HIDDEN MARKOV MODELS
• MinimumEntropy Data Partitioning using Reversible Jump Markov Chain Monte Carlo
• Independent Component Analysis: A flexible nonlinearity and decorrelating manifold approach
• Inferring the eigenvalues of covariance matrices from limited, noisy data
• Sampling distribution of the SAM statistic Technical Report No. PARG0401
• Nonstationary Logistic Regression William D. Penny and Stephen J. Roberts
• Bayesian Image Super-resolution, Continued Lyndsey C. Pickup, David P. Capel
• Gaussian Process Segmentation of Co-Moving Steven Reece
• An Entangled Bayesian Gestalt: Mean-field, Monte-Carlo and
• The Near Constant Acceleration Gaussian Process Kernel for Tracking
• Sequential Bayesian Estimation for Adaptive Classification
• Wavelet-based Voice Morphing ORPHANIDOU C.,
• Unsupervised Learning of Ranking Functions for High-Dimensional Data
• Adaptive BCI based on variational Bayes: an empirical evaluation
• A probabilistic approach to highresolution sleep P. Sykacek 1 , S. Roberts 1 , I. Rezek 1 , A. Flexer 2 , and G. Dorffner 2
• Neural Networks for Predicting Kaposi's Sarcoma Dirk Husmeier, Stephen J. Roberts, Gillian S. Patton, Myra O. McClure
• Independent Components Analysis Richard Everson and Stephen J. Roberts \Lambda
• Nonstationary Independent Component Analysis
• Gene Microarray Analysis using Angular Distribution Decomposition
• DRUM'N'BAYES: ON-LINE VARIATIONAL INFERENCE FOR BEAT TRACKING AND RHYTHM RECOGNITION
• AUTOMATED ASSESSMENT OF VIGILANCE USING COMMITTEES OF RADIAL BASIS FUNCTION ANALYSERS
• Learning Interaction Dynamics with Coupled Hidden Markov Iead Rezek, Peter Sykacek, Stephen J. Roberts
• Neural network predictions with error bars \Lambda William D. Penny and Stephen J. Roberts
• Compact Hough Transform and a Maximum Likelihood Approach to Cell Nuclei Detection
• Nonstationary Independent Component Analysis
• To appear: Statistical Science, Special Issue on Bayesian Statistics. Graphical Models
• 100 IEEE TRANSACTIONS ON SIGNAL PROCESSING, VOL. XX, NO. Y, MONTH 2001 A Tutorial on Particle Filters for On-line
• THE USE OF NEURAL NETWORKS IN EEG ANALYSIS Stephen J. Roberts y , Milos Krkic y , Iead Rezek y , James Pardey z ,
• Machine Learning Research Group Robotics Research Group
• Real-Time Information Processing of Environmental Sensor Network Data using
• Mon. Not. R. Astron. Soc. 000, 113 (2002) Printed 29 September 2011 (MN LATEX style file v2.2) A Gaussian process framework for modelling instrumental
• arXiv:1111.6399v1[astro-ph.IM]28Nov2011 **Volume Title**
• Astronomy & Astrophysics manuscript no. mcquillanetal2011 c ESO 2011 December 19, 2011