Data Fusion in 3D Through Surface Tracking. - Jonathan Shapiro; Peter Mowforth (IEA/AIE (Vol. 1), 1990)

3D Data fusion for a mobile robot. - Peter Mowforth; Jonathan Shapiro (IROS, 1990)

An Interactive Colour Line Recognition System for Seismic Section Digitisation. - Jonathan Shapiro; Zhengping Jin (MVA, 1990)

Non-Linear Statistical Analysis and Self-Organizing Hebbian Networks. - Jonathan L. Shapiro; Adam Prügel-Bennett (NIPS, 1993)

A Statistical Mechanical Formulation of the Dynamics of Genetic Algorithms. - Jonathan Shapiro; Adam Prügel-Bennett; Magnus Rattray (Evolutionary Computing, AISB Workshop, 1994)

Maximum Entropy Analysis of Genetic Algorithm Operators. - Jonathan L. Shapiro; Adam Prügel-Bennett (Evolutionary Computing, AISB Workshop, 1995)

Noisy Fitness Evaluation in Genetic Algorithms and the Dynamics of Learning. - Magnus Rattray; Jonathan Shapiro (FOGA, 1996)

Genetic Algorithm Dynamics in a Two-well Potential. - Jonathan Shapiro; Adam Prügel-Bennett (FOGA, 1996)

Use of an Artificial Neural Network in Estimating Prevalence and Assessing Underdiagnisis of Asthma. - Sybil Hirsch; Jonathan L. Shapiro; Peter I. Frank (Neural Comput. Appl., 1997)

Does Data-Model Co-evolution Improve Generalization Performance of Evolving Learners? - Jonathan L. Shapiro (PPSN, 1998)

Learning Globally Consistent Maps by Relaxation. - Tom Duckett; Stephen Marsland; Jonathan Shapiro (ICRA, 2000)

A Simple Model Exhibiting Scalar Timing. - Jonathan L. Shapiro; John Wearden; Rossano Barone (NCPW, 2000)

Novelty Detection for Robot Neotaxis - Stephen Marsland; Ulrich Nehmzow; Jonathan Shapiro (CoRR, 2000)

A Real-Time Novelty Detector for a Mobile Robot - Stephen Marsland; Ulrich Nehmzow; Jonathan Shapiro (CoRR, 2000)

Novelty Detection on a Mobile Robot Using Habituation - Stephen Marsland; Ulrich Nehmzow; Jonathan Shapiro (CoRR, 2000)

Genetic Algorithms in Machine Learning. - Jonathan L. Shapiro (Machine Learning and Its Applications, 2001)

The Importance of Selection Mechanisms in Distribution Estimation Algorithms. - Andrew Johnson; Jonathan L. Shapiro (Artificial Evolution, 2001)

Reinforcement Learning and Time Perception – a Model of Animal Experiments. - Jonathan L. Shapiro; John Wearden (NIPS, 2001)

The Sensitivity of PBIL to Its Learning Rate, and How Detailed Balance Can Remove It. - Jonathan L. Shapiro (FOGA, 2002)

Scaling of Probability-Based Optimization Algorithms. - Jonathan L. Shapiro (NIPS, 2002)

Fast, On-Line Learning of Globally Consistent Maps. - Tom Duckett; Stephen Marsland; Jonathan Shapiro (Auton. Robots, 2002)

A self-organising network that grows when required. - Stephen Marsland; Jonathan Shapiro; Ulrich Nehmzow (Neural Networks, 2002)

Sensory Anticipation for Autonomous Selection of Robot Landmarks. - Jason Fleischer; Stephen Marsland; Jonathan Shapiro (ABiALS, 2003)

A Spiking Neural Sparse Distributed Memory Implementation for Learning and Predicting Temporal Sequences. - Joy Bose; Stephen B. Furber; Jonathan L. Shapiro (ICANN (1), 2005)

An associative memory for the on-line recognition and prediction of temporal sequences. - Joy Bose; Steve B. Furber; Jonathan L. Shapiro (IJCNN, 2005)

Choosing Search Algorithms in Bayesian Optimization Algorithm. - Hao Wu; Jonathan L. Shapiro (IEC (Prague), 2005)

A System for Transmitting a Coherent Burst of Activity Through a Network of Spiking Neurons. - Joy Bose; Stephen B. Furber; Jonathan L. Shapiro (WIRN/NAIS, 2005)

Drift and Scaling in Estimation of Distribution Algorithms. - Jonathan L. Shapiro (Evol. Comput., 2005)

On-line novelty detection for autonomous mobile robots. - Stephen Marsland; Ulrich Nehmzow; Jonathan Shapiro (Robotics Auton. Syst., 2005)

Programming language challenges in systems codes: why systems programmers still use C, and what to do about it. - Jonathan Shapiro (PLOS, 2006)

Does overfitting affect performance in estimation of distribution algorithms. - Hao Wu; Jonathan L. Shapiro (GECCO, 2006)

Model Complexity vs. Performance in the Bayesian Optimization Algorithm. - Elon Santos Correa; Jonathan L. Shapiro (PPSN, 2006)

Diversity Loss in General Estimation of Distribution Algorithms. - Jonathan L. Shapiro (PPSN, 2006)

Addressing sampling errors and diversity loss in UMDA. - Jürgen Branke; Clemens Lode; Jonathan L. Shapiro (GECCO, 2007)

Parameter cross-validation and early-stopping in univariate marginal distribution algorithm. - Hao Wu; Jonathan L. Shapiro (GECCO, 2007)

Implementing Classical Conditioning with Spiking Neurons. - Chong Liu; Jonathan Shapiro (ICANN (1), 2007)

Sparse Distributed Memory Using Rank-Order Neural Codes. - Stephen B. Furber; Gavin Brown 001; Joy Bose; J. Mike Cumpstey; P. Marshall; Jonathan L. Shapiro (IEEE Trans. Neural Networks, 2007)

Modeling Failure Propagation in Large-Scale Engineering Networks. - Markus Schläpfer; Jonathan L. Shapiro (Complex (2), 2009)

Stability of learning dynamics in two-agent, imperfect-information games. - John Michael Butterworth; Jonathan L. Shapiro (FOGA, 2009)

10361 Abstracts Collection and Executive Summary - Theory of Evolutionary Algorithms. - Anne Auger; Jonathan L. Shapiro; L. Darrell Whitley; Carsten Witt (Theory of Evolutionary Algorithms, 2010)

Bayesian Mixture Models for Frequent Itemset Discovery - Ruefei He; Jonathan Shapiro (CoRR, 2012)

Thompson Sampling in Switching Environments with Bayesian Online Change Detection. - Joseph Charles Mellor; Jonathan Shapiro (AISTATS, 2013)

Opponent Modelling by Sequence Prediction and Lookahead in Two-Player Games. - Richard Mealing; Jonathan L. Shapiro (ICAISC (2), 2013)

Thompson Sampling in Switching Environments with Bayesian Online Change Point Detection - Joseph Charles Mellor; Jonathan Shapiro (CoRR, 2013)

Theory of Evolutionary Algorithms (Dagstuhl Seminar 13271). - Benjamin Doerr; Nikolaus Hansen; Jonathan L. Shapiro; L. Darrell Whitley (Dagstuhl Reports, 2013)

Smartphone Use and Acceptability Among Clinical Medical Students: A Questionnaire-Based Study. - Tim Robinson; Thomas Cronin; Haider Ibrahim; Mark Jinks; Timothy Molitor; Joshua Newman; Jonathan Shapiro (J. Medical Syst., 2013)

Detecting and reducing redundancy in alarm networks. - Timothy D. Butters; Stefan Güttel; Jonathan L. Shapiro (CASE, 2015)

Convergence of Strategies in Simple Co-Adapting Games. - Richard Mealing; Jonathan L. Shapiro (FOGA, 2015)

Run-Time Analysis of Population-Based Evolutionary Algorithm in Noisy Environments. - Adam Prügel-Bennett; Jonathan E. Rowe; Jonathan Shapiro (FOGA, 2015)

Opponent Modeling by Expectation-Maximization and Sequence Prediction in Simplified Poker. - Richard Mealing; Jonathan L. Shapiro (IEEE Trans. Comput. Intell. AI Games, 2017)

A Bayesian Approach to Dealing with Device Heterogeneity in an Indoor Positioning System. - Kyle F. Davies; Ian G. Jones; Jonathan L. Shapiro (IPIN, 2018)

Visual Question Answering as a Multi-Task Problem. - Amelia Elizabeth Pollard; Jonathan L. Shapiro (CoRR, 2020)

Eliminating Catastrophic Interference with Biased Competition. - Amelia Elizabeth Pollard; Jonathan L. Shapiro (CoRR, 2020)

Pre-treatment of outliers and anomalies in plant data: Methodology and case study of a Vacuum Distillation Unit. - Kamil Oster; Stefan Güttel; Jonathan L. Shapiro; Lu Chen; Megan Jobson (CoRR, 2021)

Machine Learning-Based Soft Sensors for Vacuum Distillation Unit. - Kamil Oster; Stefan Güttel; Lu Chen; Jonathan L. Shapiro; Megan Jobson (CoRR, 2021)