Christopher M. Bishop

66 papers A 9B 1C 2Journal 23Unranked 25
YearRankTypeTitle / Venue / Authors
2026 J jnl
Enhanced Diffusion Sampling: Efficient Rare Event Sampling and Free Energy Calculation with Diffusion Models.
CoRR
Yu Xie, Ludwig Winkler, Lixin Sun, Sarah Lewis, Adam Evan Foster, José Jiménez-Luna, Tim Hempel, Michael Gastegger, Yaoyi Chen, Iryna Zaporozhets, Cecilia Clementi, Christopher M. Bishop, Frank Noé
2025 J jnl
A Scientific Reasoning Model for Organic Synthesis Procedure Generation.
CoRR
Guoqing Liu, Junren Li, Zihan Zhao, Eray Inanc, Krzysztof Maziarz, José Garrido Torres, Victor Garcia Satorras, Shoko Ueda, Christopher M. Bishop, Marwin H. S. Segler
2025 J jnl
Accurate and scalable exchange-correlation with deep learning.
CoRR
Giulia Luise, Chin-Wei Huang, Thijs Vogels, Derk P. Kooi, Sebastian Ehlert, Stephanie Lanius, Klaas J. H. Giesbertz, Amir Karton, Deniz Gunceler, Megan Stanley, Wessel P. Bruinsma, Lin Huang, Xinran Wei, José Garrido Torres, Abylay Katbashev, Rodrigo Chavez Zavaleta, Bálint Máté, Sékou-Oumar Kaba, Roberto Sordillo, Yingrong Chen, David B. Williams-Young, Christopher M. Bishop, Jan Hermann, Rianne van den Berg, Paola Gori-Giorgi
2024 — book
Deep Learning - Foundations and Concepts
Christopher M. Bishop, Hugh Bishop
2014 — ch.
Neural Networks.
Computing Handbook, 3rd ed. (1)
Michael I. Jordan, Christopher M. Bishop
2014 — conf
Students, Teachers, Exams and MOOCs: Predicting and Optimizing Attainment in Web-Based Education Using a Probabilistic Graphical Model.
ECML/PKDD (3)
Bar Shalem, Yoram Bachrach, John Guiver, Christopher M. Bishop
2013 J jnl
Mixture Representations for Inference and Learning in Boltzmann Machines
CoRR
Neil D. Lawrence, Christopher M. Bishop, Michael I. Jordan
2013 A conf
Structural Expectation Propagation (SEP): Bayesian structure learning for networks with latent variables.
AISTATS
Nevena Lazic, Christopher M. Bishop, John M. Winn
2013 J jnl
Variational Relevance Vector Machines
CoRR
Christopher M. Bishop, Michael E. Tipping
2012 J jnl
Bayesian Hierarchical Mixtures of Experts
CoRR
Christopher M. Bishop, Markus Svensén
2011 — conf
Embracing Uncertainty: Applied Machine Learning Comes of Age.
ECML/PKDD (1)
Christopher M. Bishop
2010 — conf
Embracing Uncertainty: The New Machine Intelligence.
KES (1)
Christopher M. Bishop
2009 — ch.
A unified modeling approach to data-intensive healthcare.
The Fourth Paradigm
Iain E. Buchan, John M. Winn, Christopher M. Bishop
2008 — conf
A New Framework for Machine Learning.
WCCI
Christopher M. Bishop
2007 — book
Pattern recognition and machine learning, 5th Edition.
Christopher M. Bishop
2006 — conf
Comparison of Generative and Discriminative Techniques for Object Detection and Classification.
Toward Category-Level Object Recognition
Ilkay Ulusoy, Christopher M. Bishop
2006 — conf
Principled Hybrids of Generative and Discriminative Models.
CVPR (1)
Julia A. Lasserre, Christopher M. Bishop, Thomas P. Minka
2005 — conf
Generative versus Discriminative Methods for Object Recognition.
CVPR (2)
Ilkay Ulusoy, Christopher M. Bishop
2005 J jnl
Robust Bayesian mixture modelling.
Neurocomputing
Markus Svensén, Christopher M. Bishop
2005 — conf
The 2005 PASCAL Visual Object Classes Challenge.
MLCW
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, Tom 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
2005 J jnl
Variational Message Passing.
J. Mach. Learn. Res.
John M. Winn, Christopher M. Bishop
2004 — conf
Distinguishing text from graphics in on-line handwritten ink.
IWFHR
Christopher M. Bishop, Markus Svensén, Geoffrey E. Hinton
2004 — conf
Generative models and Bayesian model comparison for shape recognition.
IWFHR
Balaji Krishnapuram, Christopher M. Bishop, Martin Szummer
2004 — conf
Object Recognition via Local Patch Labelling.
Deterministic and Statistical Methods in Machine Learning
Christopher M. Bishop, Ilkay Ulusoy
2004 B conf
Robust Bayesian Mixture Modelling.
ESANN
Christopher M. Bishop, Markus Svensén
2003 A conf
Bayesian Hierarchical Mixtures of Experts.
UAI
Christopher M. Bishop, Markus Svensén
2003 A ed.
Proceedings of the Ninth International Workshop on Artificial Intelligence and Statistics, AISTATS 2003, Key West, Florida, USA, January 3-6, 2003
AISTATS
Christopher M. Bishop, Brendan J. Frey
2003 A conf
Structured Variational Distributions in VIBES.
AISTATS
Christopher M. Bishop, John M. Winn
2003 A conf
Super-resolution Enhancement of Video.
AISTATS
Christopher M. Bishop, Andrew Blake, Bhaskara Marthi
2002 — conf
Bayesian Image Super-Resolution.
NIPS
Michael E. Tipping, Christopher M. Bishop
2002 — conf
VIBES: A Variational Inference Engine for Bayesian Networks.
NIPS
Christopher M. Bishop, David J. Spiegelhalter, John M. Winn
2001 J jnl
Feature representation and signal classification in fluorescence in-situ hybridization image analysis.
IEEE Trans. Syst. Man Cybern. Part A
Boaz Lerner, William F. Clocksin, Seema Dhanjal, Maj A. Hultén, Christopher M. Bishop
2001 A conf
Hyperparameters for Soft Bayesian Model Selection.
AISTATS
Adrian Corduneanu, Christopher M. Bishop
2001 — conf
Optimising Synchronisation Times for Mobile Devices.
NIPS
Neil D. Lawrence, Antony I. T. Rowstron, Christopher M. Bishop, M. J. Taylor
2001 A conf
Probabilistic Modelling of Replica Divergence.
HotOS
Antony I. T. Rowstron, Neil D. Lawrence, Christopher M. Bishop
2000 — conf
Non-linear Bayesian Image Modelling.
ECCV (1)
Christopher M. Bishop, John M. Winn
2000 A conf
Variational Relevance Vector Machines.
UAI
Christopher M. Bishop, Michael E. Tipping
1999 J jnl
Mixtures of Probabilistic Principal Component Analysers.
Neural Comput.
Michael E. Tipping, Christopher M. Bishop
1999 J jnl
Neural Network-Based Wind Vector Retrieval from Satellite Scatterometer Data.
Neural Comput. Appl.
Dan Cornford, Ian T. Nabney, Christopher M. Bishop
1998 J jnl
A Hierarchical Latent Variable Model for Data Visualization.
IEEE Trans. Pattern Anal. Mach. Intell.
Christopher M. Bishop, Michael E. Tipping
1998 — conf
Bayesian PCA.
NIPS
Christopher M. Bishop
1998 J jnl
Developments of the generative topographic mapping.
Neurocomputing
Christopher M. Bishop, Markus Svensén, Christopher K. I. Williams
1998 J jnl
GTM: The Generative Topographic Mapping.
Neural Comput.
Christopher M. Bishop, Markus Svensén, Christopher K. I. Williams
1998 — ch.
Latent Variable Models.
Learning in Graphical Models
Christopher M. Bishop
1998 A conf
Mixture Representations for Inference and Learning in Boltzmann Machines.
UAI
Neil D. Lawrence, Christopher M. Bishop, Michael I. Jordan
1997 — conf
Approximating Posterior Distributions in Belief Networks Using Mixtures.
NIPS
Christopher M. Bishop, Neil D. Lawrence, Tommi S. Jaakkola, Michael I. Jordan
1997 J jnl
Bayesian Neural Networks.
J. Braz. Comput. Soc.
Christopher M. Bishop
1997 — conf
Ensemble Learning for Multi-Layer Networks.
NIPS
David Barber, Christopher M. Bishop
1997 — ch.
Neural Networks.
The Computer Science and Engineering Handbook
Michael I. Jordan, Christopher M. Bishop
1997 — conf
Regression with Input-dependent Noise: A Gaussian Process Treatment.
NIPS
Paul W. Goldberg, Christopher K. I. Williams, Christopher M. Bishop
1996 C conf
Bayesian Inference of Noise Levels in Regression.
ICANN
Christopher M. Bishop, Cazhaow S. Quazaz
1996 — conf
Bayesian Model Comparison by Monte Carlo Chaining.
NIPS
David Barber, Christopher M. Bishop
1996 C conf
GTM: A Principled Alternative to the Self-Organizing Map.
ICANN
Christopher M. Bishop, Markus Svensén, Christopher K. I. Williams
1996 — conf
GTM: A Principled Alternative to the Self-Organizing Map.
NIPS
Christopher M. Bishop, Markus Svensén, Christopher K. I. Williams
1996 J jnl
Modeling Conditional Probability Distributions for Periodic Variables.
Neural Comput.
Christopher M. Bishop, Ian T. Nabney
1996 J jnl
Neural Networks.
ACM Comput. Surv.
Michael I. Jordan, Christopher M. Bishop
1996 — conf
Regression with Input-Dependent Noise: A Bayesian Treatment.
NIPS
Christopher M. Bishop, Cazhaow S. Quazaz
1995 — conf
EM Optimization of Latent-Variables Density Models.
NIPS
Christopher M. Bishop, Markus Svensén, Christopher K. I. Williams
1995 J jnl
Real-Time Control of a Tokamak Plasma Using Neural Networks.
Neural Comput.
Christopher M. Bishop, Paul S. Haynes, Mike E. U. Smith, Tom N. Todd, David L. Trotman
1995 J jnl
Training with Noise is Equivalent to Tikhonov Regularization.
Neural Comput.
Christopher M. Bishop
1994 — conf
Estimating Conditional Probability Densities for Periodic Variables.
NIPS
Christopher M. Bishop, Claire Legleye
1994 J jnl
Fast Feedback Control of a High Temperature Fusion Plasma.
Neural Comput. Appl.
Christopher M. Bishop, Paul S. Haynes, Mike E. U. Smith, Tom N. Todd, David L. Trotman
1994 — conf
Real-Time Control of a Tokamak Plasma Using Neural Networks.
NIPS
Christopher M. Bishop
1993 J jnl
Curvature-driven smoothing: a learning algorithm for feedforward networks.
IEEE Trans. Neural Networks
Christopher M. Bishop
1993 J jnl
Reconstruction of Tokamak Density Profiles Using Feedforward Networks.
Neural Comput. Appl.
Christopher M. Bishop, Iain Strachan, John O'Rourke, Geoff Maddison, Paul Thomas
1991 J jnl
A Fast Procedure for Retraining the Multilayer Perceptron.
Int. J. Neural Syst.
Christopher M. Bishop