Chris Bishop
Impact in
- Artificial Intelligence top 0.05%
- Neural Networks and Applications
- Bayesian Methods and Mixture Models
- Gaussian Processes and Bayesian Inference
- Anomaly Detection Techniques and Applications
- Signal Processing top 0.1%
- Blind Source Separation Techniques
Papers in
-
- Neural Networks and Applications 17
- Gaussian Processes and Bayesian Inference 13
- Bayesian Methods and Mixture Models 11
- Bayesian Modeling and Causal Inference 10
- Machine Learning and Algorithms 6
- Classics 4
- Co-authors
- Michael E. TippingJohn WinnMarkus SvensénChristopher K. I. WilliamsIain BuchanAdrian CorduneanuDavid BarberAdnan Ćustović
- Journals
- Journal of Allergy and Clinical Immunology (2 papers)Film Quarterly (2 papers)Neural Computation (2 papers)Neurocomputing (2 papers)Journal of Molluscan Studies (2 papers)
- Partner nations
- United KingdomUnited StatesAustralia
In The Last Decade
Chris Bishop
87 papers receiving 22.8k citations
Hit Papers
Peers
Comparison fields: 5 of 237
- Artificial Intelligence 9.2k
- Signal Processing 3.0k
- Computer Vision and Pattern Recognition 5.4k
- Computational Mathematics 89
- Statistics and Probability 1.0k
Countries citing papers authored by Chris Bishop
This map shows the geographic impact of Chris Bishop's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Chris Bishop with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chris Bishop more than expected).
Fields of papers citing papers by Chris Bishop
This network shows the impact of papers produced by Chris Bishop. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Chris Bishop. The network helps show where Chris Bishop may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Chris Bishop, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Structural Expectation Propagation (SEP): Bayesian Structure Learning for Networks with Latent Variables | 2013 | 4 |
| 2 | Broad vs Narrow: Modelling Strategies for Online Behavioural Targeting | 2011 | 1 |
| 3 | Beowulf: The monsters and the comics | 2011 | 1 |
| 4 | Pattern Recognition and Machine Learning, 2006 | 2007 | 301 |
| 5 | Uncer Giedd Geador: The Shadows of History in Wulf and Eadwacer | 2007 | 1 |
| 6 | Pattern Recognition and Machine Learning (Information Science and Statistics) Hit paper breakdown → | 2006 | 5659 |
| 7 | Variational Message Passing Hit paper breakdown → | 2005 | 415 |
| 8 | The Erotic Poetry of the Exeter Book | 2005 | 1 |
| 9 | Structured Variational Distributions in VIBES | 2003 | 23 |
| 10 | Super-resolution Enhancement of Video | 2003 | 84 |
| 11 | Bayesian Image Super-Resolution | 2002 | 149 |
| 12 | VIBES: A Variational Inference Engine for Bayesian Networks | 2002 | 57 |
| 13 | Generalization in Neural Networks and Machine Learning | 2001 | 5 |
| 14 | Variational Bayesian Model Selection for Mixture Distributions | 2001 | 231 |
| 15 | Hyperparameters for Soft Bayesian Model Selection. | 2001 | 14 |
| 16 | Neural networks and machine learning | 1998 | 198 |
| 17 | Proceedings 1997 Workshop on Self-Organizing Maps | 1997 | 17 |
| 18 | Approximating Posterior Distributions in Belief Networks Using Mixtures | 1997 | 34 |
| 19 | Regression with Input-Dependent Noise: A Bayesian Treatment | 1996 | 29 |
| 20 | Bayesian Model Comparison by Monte Carlo Chaining | 1996 | 5 |
About Chris Bishop
Chris Bishop is a scholar working on Artificial Intelligence, Classics, Statistics and Probability, Music and Computer Vision and Pattern Recognition, having authored 100 papers that have together received 24.0k indexed citations. Recurring topics across this work include Neural Networks and Applications (17 papers), Gaussian Processes and Bayesian Inference (13 papers), Bayesian Methods and Mixture Models (11 papers), Bayesian Modeling and Causal Inference (10 papers), Machine Learning and Algorithms (6 papers), Face and Expression Recognition (6 papers), Fault Detection and Control Systems (5 papers) and Statistical Methods and Bayesian Inference (5 papers). The work is most often cited by research in Artificial Intelligence (9.2k citations), Signal Processing (3.0k citations), Computer Vision and Pattern Recognition (5.4k citations), Computational Mathematics (89 citations) and Statistics and Probability (1.0k citations). Chris Bishop has collaborated with scholars based in United Kingdom, United States and Australia. Frequent co-authors include Michael E. Tipping, John Winn, Markus Svensén, Christopher K. I. Williams, Iain Buchan, Adrian Corduneanu, David Barber, Adnan Ćustović, Angela Simpson and Paul W. Goldberg. Their work appears in journals such as Journal of Allergy and Clinical Immunology, Film Quarterly, Neural Computation, Neurocomputing and Journal of Molluscan Studies.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.