Publications

  • Trajectories of Lung Function During ChildhoodBelgrave D, Buchan I, Bishop CM, Lowe L, Simpson A, Custovic A (2014). Accepted for publication in the American Journal of Respiratory and Critical Care Medicine.
  • Changing how Earth System Modelling is Done to Provide More Useful Information for Decision Making, Science and SocietySmith M, Palmer P, Purves D, Vanderwel M, Lyutsarev V, Calderhead B, Joppa L, Bishop CM, Emmott S (2014). Accepted for publication in the Bulletin of the American Meteorological Society.
  • Artificial Life Bishop CM (2014). To appear in Life, edited by William Brown and Andrew C. Fabian Cambridge University Press PDF
  • Multiple Atopy Phenotypes and Their Associations with Asthma: Similar Findings From Two Birth Cohorts Lazic N, Roberts G, Custovic A, Belgrave D, Bishop CM, Winn J, Curtin JA, Hasan Arshad S, Simpson A (2013). Allergy 68, No. 6, pp 764 – 770. PDF
  • A Graphical Approach to Missing Data in Longitudinal Analysis Using Infer.net. Belgrave D, Bishop CM, Guiver J, Buchan I (2013). International Society of Clinical Biostatisticians, Munich. To appear.
  • Structural Expectation Propagation (SEP): Bayesian Structure Learning for Networks with Latent Variables Lazic N, Bishop C. M., Winn J (2013). In Proceedings Sixteenth International Conference on Artificial Intelligence and Statistics (AIStats), Scottsdale, Arizona. Journal of Machine Learning Research: Workshop and Conference Proceedings, 31, pp 379–387. PDF
  • Model-Based Machine Learning Bishop C. M. (2013). Philosophical Transactions of the Royal Society A, 371, pp 1–17 PDF
  • Bayesian Machine Learning Approaches for Longitudinal Latent Class Modelling to Define Wheezing Phenotypes to Elucidate Genetic and Environmental Predisposition Belgrave D, Bishop CM, Buchan IA (2012). Methods and models for Latent Variables Conference, Naples. Quaderni di Statistica", vol.14. ISBN-13 978-88-207-5364-1 PDF
  • A Comparison of Bayesian and Frequentist Methods for Identifying Markers of Susceptibility to Asthma Belgrave D, Bishop CM, Custovic A, Simpson A, Semic-Jusufagic A, Pickles A, Buchan I (2011). Proceedings of the International Workshop of Statistical Modelling, Valencia. P 75–78 . ISBN 978-84-694-5129-8. PDF
  • Broad versus Narrow: Modelling Strategies for Online Behavioural Targeting Svensén M, Xu Q, Stern D, Hanks S, Bishop C M (2011). In Proceedings of the Fifth International Workshop on Data Mining and Audience Intelligence for Advertising (ADKDD), San Diego, USA, ACM Press, 2011. PDF
  • A Stochastic Six-Degree-of-Freedom Flight Simulator for Passively Controlled High-Power Rockets In Journal of Aerospace Engineering, 24, No.1, pp31-45. Web
  • Beyond Atopy: Multiple Patterns of Sensitization in Relation to Asthma in a Birth Cohort Study A Simpson,  V. Y. F. Tan V, J. Winn, M. Svensén, C. M. Bishop, D. E. Heckerman, I. Buchan, and A. Custovic (2010). In American Journal of Respiratory and Critical Care Medicine, June, 181, 1200–1206.
  • A Unified Modelling Approach to Data-intensive Healthcare I. Buchan, I. Winn, and C. M. Bishop (2009). In Data Intensive Computing: The Fourth Paradigm of Scientific Discovery. Web | PDF
  • Healthcare e-Labs: Opening and Integrating Models of Health Buchan I, Ainsworth J, Hoyle D, Delderfield M, Smith G, Kitching L, New J, Goble C, Winn J, Bishop C. M. (2009). Proceedings of Microsoft E-Science workshop 2009. Web
  • A New Framework for Machine Learning Bishop, C. M. (2008). In computational Intelligence: Research Frontiers, IEEE World Congress on Computational Intelligence, WCCI 2008, Hong Kong, June 2008 Lecture Notes in Computer Science LNCS 5050, 1–24. Springer. PDF
  • Generative or Discriminative? Getting the Best of Both Worlds Bishop, C. M. and Lasserre, J. (2007). In Bayesian Statistics 8,  Bernardo, J. M. et al. (Eds), Oxford University Press. 3–23. With discussion. PDF
  • Pattern Recognition and Machine Learning Bishop, C. M. (2006) Springer. Web
  • Principled Hybrids of Generative and Discriminative Models Lasserre, J.  Bishop, C. M. and  Minka, T. (2006). In Proceedings 2006 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), New York. PDF
  • The 2005 PASCAL Visual Object Classes Challenge Everingham, M. Bishop, C. M. et al. (2006). In Machine Learning Challenges, J. Quinonero-Candella et al. (Eds), 117-176, Springer. PDF
  • Discriminative Writer Adaptation Szummer, M. and  Bishop, C. M. (2006). In 10th International Workshop on Frontiers in Handwriting Recognition (IWFHR).
  • Prediction Machines Bishop, C. M.  Muggleton, S. Kuppermann, A.  Moin, P. and  Ferguson, N. (2006). In  Emmott, S.  and  Rison, S. (Eds.), 2020 Science, pp. 34–35. Microsoft Research. Web | PDF
  • Variational Message Passing Winn, J. and  Bishop, C. M. (2005). Journal of Machine Learning Research 6, 661–694. PDF
  • Comparison of Generative and Discriminative Techniques for Object Detection and Classification Ulusoy, I. and Bishop, C.M. (2005a). In Ponce, C. S. J. Herbert, M. and  Zisserman, A. (Eds.), Proceedings Sicily Workshop on Object Recognition., Sicily. To appear. PDF
  • Generative versus Discriminative Methods for Object Recognition Ulusoy, I. and Bishop, C. M. (2005b). In Proceedings IEEE International Conference on Computer Vision and Pattern Recognition, CVPR., San Diego. PDF
  • Object Recognition via Local Patch Labelling Bishop, C. M. and Ulusoy, I. (2005). In Winkler, J.   Niranjan, M. and  Lawrence, N. (Eds.), Proceedings 2004 Workshop on Machine Learning, Sheffield, pp. 1–21. Springer. PDF
  • Distinguishing Text from Graphics in On-line Handwritten Ink Bishop, C. M. Svensén, M. and  Hinton, G. E. (2004). In  Kimura, F. and Fujisawa, H. (Eds.), Proceedings Ninth International Workshop on Frontiers in Handwriting Recognition, IWFHR-9, Tokyo, Japan, pp. 142–147. PDF
  • Generative Models and Bayesian Model Comparison for Shape Recognition Krishnapuram, B. Bishop, C. M. and  Szummer, M. (2004). In  Kimura, F. and Fujisawa, H. (Eds.), Proceedings Ninth International Workshop on Frontiers in Handwriting Recognition, IWFHR-9, Tokyo, Japan, pp.  20–25. PDF
  • Robust Bayesian Mixture Modelling Svensén, M. and  Bishop, C. M. (2004). Neurocomputing  64, 235–252. PDF
  • Robust Bayesian Mixture Modelling Bishop, C. M. and Svensén, M. (2004). In Verleysen, M. (Ed.), Proceedings Twelfth European Symposium on Artificial Neural Networks, pp. 69–74. d-side. PDF
  • Clumps, Clusters and Classification Bishop, C. M. (2004). In  Herbert, A. and Jones, K. S. (Eds.), Computer Systems: Theory, Technology and Applications. A Tribute to Roger Needham,Computer Monographs, pp. 39–49. Springer. Web
  • Variational Inference Engine for Probabalistic Graphical Models
    Bishop, C. M. Winn, J. Spiegelhalter, D. J. United States Patent. PDF
  • Bayesian Hierarchical Mixtures of Experts Bishop, C. M. and Svensén, M. (2003). In  Kjaerulff, U. and Meek, C. (Eds.), Proceedings Nineteenth Conference on Uncertainty in Artificial Intelligence, pp. 57–64. Morgan Kaufmann. PDF
  • Proceedings Ninth International Workshop on Artificial Intelligence and Statistics Bishop, C. M. and Frey, B. (Eds.) (2003. January 3 - 6, Key West, Florida, Published on CD-ROM and on-line. Web
  • Super-resolution Enhancement of Vide Bishop, C. M. Blake, A. and Marthi, B. (2003). In  Bishop, C. M. and  Frey, B. (Eds.), Proceedings Artificial Intelligence and Statistics, Key West, Florida. Society for Artificial Intelligence and Statistics. ISBN 0-9727358-0-1. PDF
  • Structured Variational Distributions in VIBES Bishop, C. M. and Winn, J. (2003). In Bishop, C. M.  and Frey, B. (Eds.), Proceedings Artificial Intelligence and Statistics, Key West, Florida. Society for Artificial Intelligence and Statistics. ISBN 0-9727358-0-1. PDF
  • Bayesian Regression and Classification Bishop, C. M. and Tipping, M. E. (2003). In Suykens, J. Horvath, G. Basu, S. Micchelli, C. and  Vandewalle J. (Eds.), Advances in Learning Theory: Methods, Models and Applications, Volume 190, pp.  267–285. IOS Press, NATO Science Series III: Computer and Systems Sciences. PDF
  • VIBES: A Variational Inference Engine for Bayesian Networks Bishop, C. M. Spiegelhalter, D. and  Winn, J. (2003). In  Becker, S. Thrun, S. and Obermeyer K. (Eds.), Advances in Neural Information Processing Systems, Volume 15, pp. 793–800. MIT Press. PDF
  • Bayesian Image Super-resolution Tipping, M. E. and  Bishop, C. M. (2003). In Becker, S. Thrun, S. and  Obermeyer, K. (Eds.), Advances in Neural Information Processing Systems, Volume 15, pp.  1303–1310. PDF
  • Discussion of 'Bayesian Treed Generalized Linear' by Chipman, H. A. George, E. I. and McCulloch, R. E.Bishop, C. M. (2002). In Bernardo, J. M. Bayarri, M. J. Berger, J. O. Dawid, A. P.  Heckerman, D. A. Smith, F. M. and West, M. (Eds.), Proceedings Seventh Valencia International Meeting on Bayesian Statistics, Volume 7, pp. 98–101. Oxford University Press. PDF
  • Optimising Synchronisation Times for Mobile Devices Lawrence, N. D. Rowstron, A. I. T.  Bishop, C. M. and Taylor, M. J. (2002). In  Dietterich, T. G.  Becker, S. and Ghahramani, Z. (Eds.), Advances in Neural Information Processing Systems, Volume 14, pp.  1401–1408. MIT Press. PDF
  • Variational Bayesian Model Selection for Mixture Distributions Corduneanu, A. and  Bishop, C. M. (2001). In  Richardson, T. and Jaakkola, T. (Eds.), Proceedings Eighth International Conference on Artificial Intelligence and Statistics, pp. 27–34. Morgan Kaufmann. PDF
  • Probabilistic Modelling of Replica Divergence Rowstron, A. I. T.  Lawrence, N. D. and  Bishop, C. M. (2001). In HotOS 2001. PDF
  • Feature Representation for the Automatic Analysis of Fluorescence In-situ Hybridization Images Lerner, B.  Clocksin, W. F.  Dhanjal, S. Hulten, M. A. and  Bishop, C. M. (2001a). IEEE Transactions on Systems, Man and Cybernetics A 31(6), 655–665. PDF
  • Automatic Signal Classification in Fluorescence In-situ Hybridization Images Lerner, B. Clocksin, W. F. Dhanjal, S.  Hulten, M. A. and  Bishop, C. M. (2001b). Cytometry 43(2), 87–93. PDF
  • Non-linear Bayesian Image Modelling Bishop, C. M. and Winn, J. (2000). In Proceedings Sixth European Conference on Computer Vision, Dublin, Volume 1, pp. 3–17. Springer. PDF
  • Variational Relevance Vector Machines Bishop, C. M. and Tipping, M. E. (2000a). In  Boutilier, C. and  Goldszmidt, M. (Eds.), Proceedings of the 16th Conference on Uncertainty in Artificial Intelligence, pp. 46–53. Morgan Kaufmann. PDF
  • Variational Relevance Vector Machines Bishop, C. M. and Tipping, M. E. (2000b). In Nunez-Anton, V.  and Ferreira, E. (Eds.), Proceedings 15th International Workshop on Statistical Modelling, Bilbao, Spain, pp. 1–17. Universidad del Pais Vasco.
  • Variational Principal Components Bishop, C. M. (1999). In Proceedings Ninth International Conference on Artificial Neural Networks, ICANN'99, Volume 1, pp.  509–514. IEE. PDF
  • Mixtures of Probabilistic Principal Component Analyzers Tipping, M. E. and  Bishop, C. M. (1999a). Neural Computation 11(2), 443–482. PDF
  • Probabilistic Principal Component Analysis Tipping, M. E. and  Bishop, C. M. (1999b). Journal of the Royal Statistical Society, Series B  21(3), 611–622. PDF
  • Neural Network-based Wind Vector Retrieval from Satellite Scatterometer Data Cornford, D. Nabney, I. T. and Bishop, C. M. (1999). Neural Computing and Applications  8, 206–217. PDF
  • Neural Network Training Using Multi-channel Data with Aggregate Labelling McGrogan, N.  Bishop, C. M. and Tarassenko, L. (1999). In Proceedings Ninth International Conference on Artificial Neural Networks, ICANN'99, Volume 2, pp.  862–867. IEE. Web
  • Pattern Recognition and Feedforward Neural Networks Bishop, C. M. (1999a). In Wilson, R. A.  and  Keil, F. C. (Eds.), The MIT Encyclopaedia of the Cognitive Sciences, pp. 629–631. MIT Press. PDF
  • Latent Variable Models Bishop, C. M. (1999b). In Jordan, M. I. (Ed.), Learning in Graphical Models, pp.  371–403. MIT Press. PDF
  • Bayesian PCA Bishop, C. M. (1999c). In Kearns, M. S. Solla, S. A. and  Cohn, D. A. (Eds.), Advances in Neural Information Processing Systems, Volume 11, pp.  382–388. MIT Press. PDF
  • Pulsed Neural Networks Maass, W. and  Bishop, C. M. (1998). MIT Press.
  • Neural Networks and Machine Learning Bishop, C. M. (1998). Springer.
  • A Hierarchical Latent Variable Model for Data Visualization Bishop, C. M. and Tipping, M. E. (1998). IEEE Transactions on Pattern Analysis and Machine Intelligence 20(3), 281–293. PDF
  • Developments of the Generative Topographic Mapping Bishop, C. M. Svensén, M. and  Williams, C. K. I. (1998). Neurocomputing  21, 203–224. PDF
  • Mixture Representations for Inference and Learning in Boltzmann Machines Lawrence, N. Bishop, C. M. and Jordan, M. (1998). In Uncertainty in Artificial Intelligence, Volume 14, pp. 320–327. Morgan Kaufmann.
  • GTM: the Generative Topographic Mapping Bishop, C. M.  Svensén, M. and Williams, C. K. I. (1998). Neural Computation  10(1), 215–234. PDF
  • Variational Learning in Graphical Models and Neural Networks Bishop, C. M. (1998). In Proceedings 8th International Conference on Artificial Neural Networks, ICANN'98, pp. 13–22. Springer. PDF
  • Ensemble Learning in Bayesian Neural Networks Barber, D. and  Bishop, C. M. (1998). In  Bishop, C. M. (Ed.), Generalization in Neural Networks and Machine Learning, pp. 215–237. Springer. PDF
  • Regression with Input-dependent Noise: A Gaussian Process Treatment Goldberg, P. W.  Williams, C. K. I. and  Bishop, C. M. (1998). In Advances in Neural Information Processing Systems, Volume 10, pp. 493–499. MIT Press. PDF
  • Approximating Posterior Distributions in Belief Networks Using Mixtures Bishop, C. M. Lawrence, N. Jaakkola, T. and  Jordan, M. I. (1998). In Advances in Neural Information Processing Systems, Volume 10, pp.  416–422. PDF
  • Ensemble Learning for Multi-layer Networks Barber, D. and Bishop, C. M. (1998). In Jordan, M. I. Kearns, K. J. and  Solla, S. A.(Eds.), Advances in Neural Information Processing Systems, Volume 10, pp. 395–401. PDF
  • Latent Variables, Topographic Mappings and Data Visualization Bishop, C. M. (1997). In  Marinaro, M. and Tagliaferri, R. (Eds.), Proceedings IX Italian Workshop on Neural Networks, Vietri sur Mare, Salerno, pp. 1–32. Springer.
  • On Computing the KL Divergence for Bayesian Neural Networks Barber, D. and Bishop, C. M. (1997). Technical report, Neural Computing Research Group, Aston University, Birmingham, U.K.
  • GTM: a Principled Alternative to the Self-Organizing Map Bishop, C. M.  Svensén, M. and Williams, C. K. I. (1997). In von der Malsburg, C. von Selen, W. Vorbruggen, J. C. and Sendhoff, B. (Eds.), International Conference on Artificial Neural Networks, ICANN'96, pp. 165–170. Springer.
  • Bayesian Inference of Noise Levels in Regression Bishop, C. M. and  Qazaz, C. S. (1997). In Proceedings 1996 International Conference on Artificial Neural Networks, ICANN'96, Bochum, Germany, pp.  59–64. Springer. PDF
  • GTM Through Time Bishop, C. M. Hinton, G. E. and  Strachan, I. G. D. (1997). In Proceedings IEE Fifth International Conference on Artificial Neural Networks, Cambridge, U.K., pp. 111–116. PDF
  • Neural Networks Jordan, M. I. and  Bishop, C. M. (1997). In  Tucker, A. B.  (Ed.), The Computer Science and Engineering Handbook, pp. 536–556. CRC Press. PDF
  • Magnification Factors for the GTM Algorithm Bishop, C. M., Svensén, M. and  Williams, C. K. I. (1997a). In Proceedings IEE Fifth International Conference on Artificial Neural Networks, Cambridge, U.K., pp. 64–69. Institute of Electrical Engineers. PDF
  • Magnification Factors for the SOM and GTM Algorithms Bishop, C. M. Svensén, M. and  Williams, C. K. I. (1997b). In Proceedings 1997 Workshop on Self-Organizing Maps, Helsinki University of Technology, Finland., pp. 333–338.
  • Mixtures of Principal Component Analysers Tipping, M. E. and  Bishop, C. M. (1997a). In Proceedings IEE Fifth International Conference on Artificial Neural Networks, Cambridge, U.K., July., pp. 13–18. London: IEE.
  • Hierarchical Models for Data Visualization Tipping, M. E. and  Bishop, C. M. (1997b). In Proceedings IEE Fifth International Conference on Artificial Neural Networks, Cambridge, U.K., pp. 70–75.
  • Latent Variable Models and Data Visualization Bishop, C. M. and Tipping, M. E. (1997). In Titterington, M. and Kay, J. (Eds.), Statistics and Neural Networks, pp. 147–164. Oxford University Press.
  • Bayesian Neural Networks Bishop, C. M. (1997). Journal of the Brazilian Computer Society  1(4), 61–68. Special issue on neural networks.
  • An Upper Bound on the Bayesian Error Bars for Generalized Linear Regression Qazaz, C. S. Williams, C. K. I  and Bishop, C. M. (1997). In  Ellacott, S. W.  Mason, J. C. and Anderson, I. J. (Eds.), Mathematics of Neural Networks: Models, Algorithms and Applications, pp.  295–299. Kluwer. PDF
  • Modelling Conditional Probability Densities for Periodic Variables Bishop, C. M. and Nabney, I. T. (1997). In Ellacott, S. W  Mason, J. C. and Anderson, I. J. (Eds.), Mathematics of Neural Networks: Models, Algorithms and Applications, pp. 118–122. Kluwer.
  • Neural Networks Bishop, C. M. (1997). In  Bullock, A. and Trombley, S. (Eds.) Fontana Dictionary of Modern Thought (Third ed.). Fontana Press.
  • Regression with Input-dependent Noise: A Bayesian Treatment Bishop, C. M. and Qazaz, C. S (1997). In Advances in Neural Information Processing Systems, Volume 9, pp. 347–353. MIT Press. PDF
  • GTM: A Principled Alternative to the Self-Organizing Map Bishop, C. M.  Svensén, M. and Williams, C. K. I. (1997). In  Mozer, M. C. Jordan, M. I. and Petche T. (Eds.) Advances in Neural Information Processing Systems, Volume 9, pp. 354–360. MIT Press. PDF
  • Bayesian Model Comparison by Monte Carlo Chaining Barber, D. and Bishop, C. M. (1997). In Mozer, M. Jordan, M. and Petsche, T. (Eds.) Advances in Neural Information Processing Systems, Volume 9, pp. 333–339. MIT Press. PDF
  • Neural Networks Jordan, M. I. and  Bishop, C. M. (1996). ACM Computing Surveys  28(1), 73–75. PDF
  • Modelling Conditional Probability Distributions for Periodic Variables Bishop, C. M. and  Nabney, I. T. (1996). Neural Computation  8(5), 1123–1133.
  • Neural Networks: A Pattern Recognition Perspective Bishop, C. M. (1996a). In  Fiesler, E. and  Beale, R. (Eds.), Handbook of Neural Computation. Oxford University Press and IOP Publishing.
  • Theoretical Foundations of Neural Networks Bishop, C. M. (1996b). In . Borcherds, P  Bubak, M. and  Maksymowicz, A.(Eds.), Proceedings of Physics Computing 96, Krakow, pp.  500–507. Academic Computer Centre.
  • EM Optimization of Latent Variable Density Models Bishop, C. M.  Svensén, M. and  Williams, C. K. I. (1996). In  Touretzky, D. S.M.  Mozer, C. and  Hasselmo, M. E. (Eds.), Advances in Neural Information Processing Systems, Volume 8, pp. 465–471. MIT Press. PDF
  • Neural Networks for Pattern RecognitionBishop, C. M. (1995a). Oxford University Press.
  • Training with Noise is Equivalent to Tikhonov Regularization Bishop, C. M. (1995b). Neural Computation 7(1), 108–116. PDF
  • Real-time Control of a Tokamak Plasma Using Neural Networks Bishop, C. M.,  Haynes, P. S.  Smith, M. E. U  Todd, T. N. and  Trotman, D. L. (1995). Neural Computation  7, 206–217. PDF
  • On the Relationship Between Bayesian Error Bars and the Input Data Density Williams, C. K. I.  Qazaz, C.  Bishop, C. M. and Zhu, H. (1995). In Proceedings Fourth IEE International Conference on Artificial Neural Networks, Cambridge, UK, pp. 160–165. IEE.
  • Modelling Conditional Probability Distributions for Periodic Variables Nabney, I. T. Bishop, C. M and Legleye, C. (1995). In Proceedings Fourth IEE International Conference on Artificial Neural Networks, Cambridge, UK, pp.  177–182. IEE.
  • Bayesian Methods for Neural Networks Bishop, C. M. (1995). Technical Report NCRG/95/009, Neural Computing Research Group, Aston University.
  • Recent Progress in the Measurement and Analysis of Ece on Jet Bartlett, D. Bishop, C. M.  Cahill, R.  McLachlan, A.  Porte, L. and Rookes, A.(1995). In Proceedings of the 9th International Workshop on ECE and ECRH.
  • Real-time Control of a Tokamak Plasma Using a Hardware Neural Network Bishop, C. M.  Haynes, P. S. Smith, M. E. U.  Todd, T. N. and  Trotman, D. L.(1995). In J. G. Taylor (Ed.), Neural Networks, Chapter 12, pp. 193–216. Alfred Waller.
  • Regularization and Complexity Control in Feed-Forward Networks Bishop, C. M. (1995a). In  Fougelman-Soulie, F.and  Gallinari, P.(Eds.), Proceedings International Conference on Artificial Neural Networks ICANN'95, Volume 1, pp.  141–148. EC2 et Cie.
  • Multiphase Flow Monitoring in Oil Pipelines Bishop, C. M. (1995b). In  Murray, A. F. (Ed.), Applications of Neural Networks, Chapter 6, pp. 133–155. Kluwer.
  • Modelling Conditional Probability Distributions for Periodic Variables Nabney, I. T. and Bishop, C. M. (1995). In  Fougelman-Soulie, F. and Gallinari, P. (Eds.), Proceedings International Conference on Artificial Neural Networks ICANN'95, Volume 2, Paris, pp.  209–214. EC2 et Cie.
  • Estimating Conditional Probability Densities for Periodic Variables Bishop, C. M. and Legleye, C. (1995). In Tesauro, G Touretzky, D. S. and  Leen, T. K. (Eds.), Advances in Neural Information Processing Systems, Volume 7, Cambridge MA, pp. 641–648. MIT Press. PDF
  • Real-time Control of a Tokamak Plasma Using Neural Networks Bishop, C. M.  Haynes, P. S. Smith, M. E. U. Todd,T. N. Trotman, D. L. and WindsoR, C. G. (1995). In Tesauro, G. Touretzky, D. S. and Leen, T. K. (Eds.)Advances in Neural Information Processing Systems, Volume 7, Cambridge MA, pp.  1007–1014. MIT Press. PDF
  • Mixture Density Networks Bishop, C. M. (1994a). Technical Report NCRG/94/004, Neural Computing Research Group, Aston University. PDF
  • Novelty detection and Neural Network Validation Bishop, C. M. (1994b). IEE Proceedings: Vision, Image and Signal Processing 141(4), 217–222. Special issue on applications of neural networks. PDF
  • Fast Feedback Control of a High Temperature Fusion Plasma Bishop, C. M. Haynes, P. S.  Smith, M. E. U. Todd, T. N.and  Trotman, D. L. (1994). Neural Computing and Applications 2(3), 148–159. PDF
  • Neural Networks and Their Applications Bishop, C. M. (1994). Review of Scientific Instruments  65(6), 1803–1832. PDF
  • An Investigation of Coupled Energy and Particle Transport in Tokamak Plasmas Deliyanakis, N. Bishop, C. M.Connor, J. W. Cox, M. and Robinson, D. C. (1994). Plasma Physics and Controlled Fusion  36(9), 1391–1406. PDF
  • Novelty Detection and Neural Network Validation Bishop, C. M. (1993). In Gielen, S. and Kappen, B.  (Eds.), Proceedings International Conference on Artificial Neural Networks ICANN'93, pp. 789–794.
  • Automatic Analysis of JET Charge Exchange Recombination Spectra Using Neural Networks Bishop, C. M. Roach, C. M. and von Hellermann, M. G. (1993). Plasma Physics and Controlled Fusion 35, 765–773. PDF
  • Analysis of Multiphase Flows Using Dual-energy Gamma Densitometry and Neural Networks Bishop, C. M. and James, G. D. (1993). Nuclear Instruments and Methods in Physics Research  A327, 580–593. PDF
  • Curvature-driven Smoothing: A Learning Algorithm for Feedforward Networks Bishop, C. M. (1993). IEEE Transactions on Neural Networks 4(5), 882–884. PDF
  • Reconstruction of Tokamak Density Profiles Using Feed-forward Networks Bishop, C. M.  Strachan, I. G. D.  O'Rourke, J. Maddison, G. P. and Thomas, P. S. (1993). Neural Computing and Applications 1(1), 4–16. PDF
  • Neural Network Validation: An Illustration from the Monitoring of Multi-phase Flows Bishop, C. M. (1993). In Proceedings IEE Conference on Artificial Neural Networks, pp. 41–45.
  • Exact Calculation of the Hessian Matrix for the Multilayer PerceptronBishop, C. M. (1992). Neural Computation  4(4), 494–501. PDF
  • Fast Curve Fitting Using Neural Networks Bishop, C. M. and Roach, C. M. (1992). Review of Scientific Instruments  63(10), 4450–4456. PDF
  • Neural Network Approach to Energy Confinement Scaling in Tokamaks Allen, L. and Bishop, C. M. (1992). Plasma Physics and Controlled Fusion 34(7), 1291–1302. PDF
  • Neural Networks and their Diagnostic Applications Bishop, C. M. (1992). Review of Scientific Instruments  63(10), 4772–4774.
  • A Neural Network Approach to Tokamak Equilibrium Control Bishop, C. M. Cox, P. Haynes, P. S. Roach, C. M. Smith, M. E. U. Todd, T. N. and Trotman, D. L. (1992). In J. G. Taylor (Ed.), Neural Network Applications, pp. 114–128. Springer.
  • Curvature-driven Smoothing in Back-propagation Neural Networks Bishop, C. M. (1992). In Taylor, J. G. and Mannion, C. L. T. (Eds.), Theory and Applications of Neural Networks, pp. 139–148. Springer.
  • Reconstruction of Tokamak Density Profiles Using Feed-forward Networks Bishop, C. M. Strachan, I. G. D. O'Rourke, J.  Maddison, G. and Thomas, P. (1992). In Aleksander, I. and Taylor, J. G. (Eds.), Artificial Neural Networks, Proceedings ICANN'92, Brighton, U.K., Volume 2, pp.  1207–1210. North Holland.
  • Hardware Implementation of a Neural Network for Plasma Position Control in Compass-d Bishop, C. M. Haynes, P.S. Roach, C. M.  Smith,  M. E. U. Todd, T. N. and Trotman, D. L. (1992). In  Fero, C. Gasparotto, M.and Knoepfel, K. (Eds.), Proceedings of the 17th Symposium on Fusion Technology, Rome, Italy, Volume 2, pp. 997–1001. Elsevier Science Publishers.
  • Improving the Generalization Properties of Radial Basis Function Neural Networks Bishop, C. M. (1991a). Neural Computation  3(4), 579–588.
  • A Fast Procedure for Retraining the Multilayer Perceptron Bishop, C. M. (1991b). International Journal of Neural Systems  2(3), 229–236. PDF
  • Book Review: Neural Networks, An Introduction by B. Muller and J. Reinhardt Bishop, C. M. (1991c). springer Computer Physics Communications  67, 357–359.
  • On the Difficulty of Determining Tearing Mode Stability Bishop, C. M.  Connor, J. W. Cowley, S. C. and  Hastie, R. J. (1991). Plasma Physics  33(4), 389–395. PDF
  • Curvature-driven Smoothing in Back-propagation Neural Networks Bishop, C. M. (1990). In Angeniol, B. and Widrow, B. (Eds.), International Neural Networks Conference, INNC'90, Volume 2, pp. 749–752. IEEE.
  • Heat-pulse Propagation in Tokamaks and the Role of Density Perturbations Bishop, C. M. and Connor, J. W. (1990). Plasma Physics  32, 203. PDF
  • Ballooning Delta-prime in the Second Stable Region Bishop, C. M. Hastie, R. J. Sykes, A. and Wilson, H. R.(1990). Physics of Fluids B2, 3052. PDF
  • Investigation of Coupled Energy and Particle Transport Bishop, C. M. Connor, J. W. Cox, M. Deliyankis, N. and  Robinson, D. C. (1990). In Proceedings 17th European Physical Society on Controlled Fusion and Plasma Heating, Amsterdam, Volume 1, pp. 178.
  • An Intelligent Shell for the Toroidal Pinch Bishop, C. M. (1989). Plasma Physics 31, 1179. PDF
  • Stability of Toroidicity Induced Drift Waves in Divertor Tokamaks Briguglio, S. Bishop, C. M.  Connor, J. W.  Hastie, R. J. and Romanelli, F. (1989). Physics of Fluids  B1, 1449.
  • Alpha Particle Induced Magnetoacoustic Instability in a Thermonuclear Plasma Bishop, C. M. Fitzpatrick, R. Hastie, R. J. and Jackson, J. C. (1989). Plasma Physics  31, 431. PDF
  • Ballooning Stability Analysis of JET H-mode Discharges O'Brien, D. P. Bishop, C. M. et al. (1989). In Proceedings 16th European Conference on Controlled Fusion and Plasma Physics, Venice, Volume 1, pp. 229.
  • Density Modulation During Modulated ECRH in DITE Bishop, C. M. et al. (1989). In Proceedings 16th European Conference on Controlled Fusion and Plasma Physics, Venice, Volume 3, pp.  1131.
  • Resistive Ballooning Modes Under Plasma Edge Conditions Grassie, K. Bishop, C. M. Hastie, R. J. Hender, T. C. and Zehrfeld, H. P. (1988). In Proceedings 15th European Conference on Controlled Fusion and Plasma Physics, Dubrovnik, Volume 1, pp. 366.
  • Direct Losses of Alpha Particles in Spin Polarised Plasmas Maddison, G. P. Hastie, R. J. and Bishop, C. M. (1988). In Proceedings 15th European Conference on Controlled Fusion and Plasma Physics, Dubrovnik, Volume 1, pp. 302.
  • Resistive Ballooning Modes and the Second Region of Stability Sykes, A. Bishop, C. M. and Hastie, R. J. (1987). Plasma Physics  29, 719. PDF
  • H-mode Confinement in JET Keilhacker, M. Bishop, C. M. Cordey, J. G. Muir, D. G. and Watkins, M. L. (1987). In Proceedings 14th European Conference on Controlled Fusion and Plasma Physics, Madrid, Volume 3, pp. 1339. JET Report JET-P(87)23.
  • Bifurcated Temperature Profiles and the H-mode Bishop, C. M. (1986a). Nuclear Fusion  27, 1765. PDF
  • Stability of Localised MHD Modes in Divertor Tokamaks - a picture of the H-mode Bishop, C. M. (1986b). Nuclear Fusion 26, 1063. PDF
  • Degenerate Toroidal Magnetohydrodynamic Equilibria and Minimum B Bishop, C. M. and Taylor, J. B. (1986). Physics of Fluids 29, 1444. PDF
  • Micro-instability Based Models for Confinement Properties and Ignition Criteria in Tokamaks Tang, W. M. Bishop, C. M. et al. (1986). In Proceedings 11th European Conference on Plasma Physics and Controlled Fusion Research, Kyoto, Volume 1, pp. 337. Princeton Report PPPL-2418.
  • Stability of Anisotropic Pressure Tokamak Equilibria to Ideal Ballooning Modes Bishop, C. M. and Hastie, R. J. (1985). Nuclear Fusion  25, 1443. PDF
  • A Special Class of Toroidal MHD Equilibria Including Minimum-B Bishop, C. M. and Taylor, J. B. (1985). In Proceedings 12 European Conference on Controlled Fusion and Plasma Physics, Budapest, pp. 401–404.
  • Ideal MHD Ballooning Stability in the Vicinity of a Separatrix Bishop, C. M. Kirby, P. Connor, J. W. Hastie, R. J.and Taylor, J. B. (1984). Nuclear Fusion  24, 1579.
  • Topological Charge Distribution in SU(N) Gauge Theories Bishop, C. M. and  Swift, P. V. D.(1983). Physics Letters  129B, 198.
  • The Semi-Classical Method in Field Theory Bishop, C. M. (1983). Ph. D. thesis, University of Edinburgh.