Christopher M. Bishop

Publication Activity (10 Years)

Years Active: 1991-2014
Publications (10 Years): 0

Top Topics

Bayesian Learning

Structure Learning

Boltzmann Machine

Expectation Propagation

Top Venues

Publications

Bar Shalem, Yoram Bachrach, John Guiver, Christopher M. Bishop
Students, Teachers, Exams and MOOCs: Predicting and Optimizing Attainment in Web-Based Education Using a Probabilistic Graphical Model. ECML/PKDD (3) (2014)
Neil D. Lawrence, Christopher M. Bishop, Michael I. Jordan
Mixture Representations for Inference and Learning in Boltzmann Machines CoRR (2013)
Nevena Lazic, Christopher M. Bishop, John M. Winn
Structural Expectation Propagation (SEP): Bayesian structure learning for networks with latent variables. AISTATS (2013)
Christopher M. Bishop, Michael E. Tipping
Variational Relevance Vector Machines CoRR (2013)
Christopher M. Bishop, Markus Svensén
Bayesian Hierarchical Mixtures of Experts CoRR (2012)
Christopher M. Bishop
Embracing Uncertainty: Applied Machine Learning Comes of Age. ECML/PKDD (1) (2011)
Christopher M. Bishop
Embracing Uncertainty: The New Machine Intelligence. KES (1) (2010)
Christopher M. Bishop
A New Framework for Machine Learning. WCCI (2008)
Christopher M. Bishop, Nasser M. Nasrabadi
. J. Electronic Imaging 16 (4) (2007)
Julia A. Lasserre, Christopher M. Bishop, Thomas P. Minka
Principled Hybrids of Generative and Discriminative Models. CVPR (1) (2006)
Ilkay Ulusoy, Christopher M. Bishop
Comparison of Generative and Discriminative Techniques for Object Detection and Classification. Toward Category-Level Object Recognition (2006)
Ilkay Ulusoy, Christopher M. Bishop
Generative versus Discriminative Methods for Object Recognition. CVPR (2) (2005)
Markus Svensén, Christopher M. Bishop
Robust Bayesian mixture modelling. Neurocomputing 64 (2005)
John M. Winn, Christopher M. Bishop
Variational Message Passing. J. Mach. Learn. Res. 6 (2005)
Mark Everingham, Andrew Zisserman, Christopher K. I. Williams, Luc Van Gool, Moray Allan, Christopher M. Bishop, Olivier Chapelle, Navneet Dalal, Thomas Deselaers, Gyuri Dorkó, Stefan Duffner, Jan Eichhorn, Jason D. R. Farquhar, Mario Fritz, Christophe Garcia, Thomas L. Griffiths, Frédéric Jurie, Daniel Keysers, Markus Koskela, Jorma Laaksonen, Diane Larlus, Bastian Leibe, Hongying Meng, Hermann Ney, Bernt Schiele, Cordelia Schmid, Edgar Seemann, John Shawe-Taylor, Amos J. Storkey, Sándor Szedmák, Bill Triggs, Ilkay Ulusoy, Ville Viitaniemi, Jianguo Zhang
The 2005 PASCAL Visual Object Classes Challenge. MLCW (2005)
Balaji Krishnapuram, Christopher M. Bishop, Martin Szummer
Generative models and Bayesian model comparison for shape recognition. IWFHR (2004)
Christopher M. Bishop, Markus Svensén, Goeffrey E. Hinton
Distinguishing text from graphics in on-line handwritten ink. IWFHR (2004)
Christopher M. Bishop, Ilkay Ulusoy
Object Recognition via Local Patch Labelling. Deterministic and Statistical Methods in Machine Learning (2004)
Christopher M. Bishop, Markus Svensén
Robust Bayesian Mixture Modelling. ESANN (2004)
Christopher M. Bishop, Andrew Blake, Bhaskara Marthi
Super-resolution Enhancement of Video. AISTATS (2003)
Christopher M. Bishop, Markus Svensén
Bayesian Hierarchical Mixtures of Experts. UAI (2003)
Christopher M. Bishop, John M. Winn
Structured Variational Distributions in VIBES. AISTATS (2003)
Christopher M. Bishop, David J. Spiegelhalter, John M. Winn
VIBES: A Variational Inference Engine for Bayesian Networks. NIPS (2002)
Michael E. Tipping, Christopher M. Bishop
Bayesian Image Super-Resolution. NIPS (2002)
Adrian Corduneanu, Christopher M. Bishop
Hyperparameters for Soft Bayesian Model Selection. AISTATS (2001)
Boaz Lerner, William F. Clocksin, Seema Dhanjal, Maj A. Hultén, Christopher M. Bishop
Feature representation and signal classification in fluorescence in-situ hybridization image analysis. IEEE Trans. Syst. Man Cybern. Part A 31 (6) (2001)
Neil D. Lawrence, Antony I. T. Rowstron, Christopher M. Bishop, M. J. Taylor
Optimising Synchronisation Times for Mobile Devices. NIPS (2001)
Antony I. T. Rowstron, Neil D. Lawrence, Christopher M. Bishop
Probabilistic Modelling of Replica Divergence. HotOS (2001)
Christopher M. Bishop, John M. Winn
Non-linear Bayesian Image Modelling. ECCV (1) (2000)
Christopher M. Bishop, Michael E. Tipping
Variational Relevance Vector Machines. UAI (2000)
Michael E. Tipping, Christopher M. Bishop
Mixtures of Probabilistic Principal Component Analysers. Neural Comput. 11 (2) (1999)
Dan Cornford, Ian T. Nabney, Christopher M. Bishop
Neural Network-Based Wind Vector Retrieval from Satellite Scatterometer Data. Neural Comput. Appl. 8 (3) (1999)
Christopher M. Bishop
Bayesian PCA. NIPS (1998)
Neil D. Lawrence, Christopher M. Bishop, Michael I. Jordan
Mixture Representations for Inference and Learning in Boltzmann Machines. UAI (1998)
Christopher M. Bishop, Michael E. Tipping
A Hierarchical Latent Variable Model for Data Visualization. IEEE Trans. Pattern Anal. Mach. Intell. 20 (3) (1998)
Christopher M. Bishop, Markus Svensén, Christopher K. I. Williams
Developments of the generative topographic mapping. Neurocomputing 21 (1-3) (1998)
Christopher M. Bishop, Markus Svensén, Christopher K. I. Williams
GTM: The Generative Topographic Mapping. Neural Comput. 10 (1) (1998)
Christopher M. Bishop, Neil D. Lawrence, Tommi S. Jaakkola, Michael I. Jordan
Approximating Posterior Distributions in Belief Networks Using Mixtures. NIPS (1997)
Christopher M. Bishop
Bayesian Neural Networks. J. Braz. Comput. Soc. 4 (1) (1997)
Paul W. Goldberg, Christopher K. I. Williams, Christopher M. Bishop
Regression with Input-dependent Noise: A Gaussian Process Treatment. NIPS (1997)
David Barber, Christopher M. Bishop
Ensemble Learning for Multi-Layer Networks. NIPS (1997)
Christopher M. Bishop, Markus Svensén, Christopher K. I. Williams
GTM: A Principled Alternative to the Self-Organizing Map. ICANN (1996)
Christopher M. Bishop, Ian T. Nabney
Modeling Conditional Probability Distributions for Periodic Variables. Neural Comput. 8 (5) (1996)
Christopher M. Bishop, Cazhaow S. Quazaz
Regression with Input-Dependent Noise: A Bayesian Treatment. NIPS (1996)
Christopher M. Bishop, Markus Svensén, Christopher K. I. Williams
GTM: A Principled Alternative to the Self-Organizing Map. NIPS (1996)
Michael I. Jordan, Christopher M. Bishop
Neural Networks. ACM Comput. Surv. 28 (1) (1996)
Christopher M. Bishop, Cazhaow S. Quazaz
Bayesian Inference of Noise Levels in Regression. ICANN (1996)
David Barber, Christopher M. Bishop
Bayesian Model Comparison by Monte Carlo Chaining. NIPS (1996)
Christopher M. Bishop, Paul S. Haynes, Mike E. U. Smith, Tom N. Todd, David L. Trotman
Real-Time Control of a Tokamak Plasma Using Neural Networks. Neural Comput. 7 (1) (1995)
Christopher M. Bishop, Markus Svensén, Christopher K. I. Williams
EM Optimization of Latent-Variables Density Models. NIPS (1995)
Christopher M. Bishop
Training with Noise is Equivalent to Tikhonov Regularization. Neural Comput. 7 (1) (1995)
Christopher M. Bishop
Real-Time Control of a Tokamak Plasma Using Neural Networks. NIPS (1994)
Christopher M. Bishop, Claire Legleye
Estimating Conditional Probability Densities for Periodic Variables. NIPS (1994)
Christopher M. Bishop, Paul S. Haynes, Mike E. U. Smith, Tom N. Todd, David L. Trotman
Fast Feedback Control of a High Temperature Fusion Plasma. Neural Comput. Appl. 2 (3) (1994)
Christopher M. Bishop
Curvature-driven smoothing: a learning algorithm for feedforward networks. IEEE Trans. Neural Networks 4 (5) (1993)
Christopher M. Bishop, Iain Strachan, John O'Rourke, Geoff Maddison, Paul Thomas
Reconstruction of Tokamak Density Profiles Using Feedforward Networks. Neural Comput. Appl. 1 (1) (1993)
Christopher M. Bishop
A Fast Procedure for Retraining the Multilayer Perceptron. Int. J. Neural Syst. 2 (3) (1991)