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Christopher K. I. Williams: [Publications] [Author Rank by year] [Co-authors] [Prefers] [Cites] [Cited by]

Publications of Author

  1. John Shawe-Taylor, Christopher K. I. Williams, Nello Cristianini, Jaz S. Kandola
    On the Eigenspectrum of the Gram Matrix and Its Relationship to the Operator Eigenspectrum. [Citation Graph (0, 0)][DBLP]
    ALT, 2002, pp:23-40 [Conf]
  2. Felix V. Agakov, Edwin V. Bonilla, John Cavazos, Björn Franke, Grigori Fursin, Michael F. P. O'Boyle, John Thomson, Marc Toussaint, Christopher K. I. Williams
    Using Machine Learning to Focus Iterative Optimization. [Citation Graph (0, 0)][DBLP]
    CGO, 2006, pp:295-305 [Conf]
  3. John Shawe-Taylor, Christopher K. I. Williams, Nello Cristianini, Jaz S. Kandola
    On the Eigenspectrum of the Gram Matrix and Its Relationship to the Operator Eigenspectrum. [Citation Graph (0, 0)][DBLP]
    Discovery Science, 2002, pp:12- [Conf]
  4. Peter Sollich, Christopher K. I. Williams
    Understanding Gaussian Process Regression Using the Equivalent Kernel. [Citation Graph (0, 0)][DBLP]
    Deterministic and Statistical Methods in Machine Learning, 2004, pp:211-228 [Conf]
  5. Nicholas J. Adams, Christopher K. I. Williams
    Dynamic Trees: Learning to Model Outdoor Scenes. [Citation Graph (0, 0)][DBLP]
    ECCV (4), 2002, pp:82-96 [Conf]
  6. Christopher M. Bishop, Markus Svensén, Christopher K. I. Williams
    GTM: A Principled Alternative to the Self-Organizing Map. [Citation Graph (0, 0)][DBLP]
    ICANN, 1996, pp:165-170 [Conf]
  7. Edwin V. Bonilla, Christopher K. I. Williams, Felix V. Agakov, John Cavazos, John Thomson, Michael F. P. O'Boyle
    Predictive search distributions. [Citation Graph (0, 0)][DBLP]
    ICML, 2006, pp:121-128 [Conf]
  8. Christopher K. I. Williams, Matthias Seeger
    The Effect of the Input Density Distribution on Kernel-based Classifiers. [Citation Graph (0, 0)][DBLP]
    ICML, 2000, pp:1159-1166 [Conf]
  9. Nicholas J. Adams, Amos J. Storkey, Christopher K. I. Williams, Zoubin Ghahramani
    MFDTs: Mean Field Dynamic Trees. [Citation Graph (0, 0)][DBLP]
    ICPR, 2000, pp:3151-3154 [Conf]
  10. Mark Everingham, Andrew Zisserman, Christopher K. I. Williams, Luc J. 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
    The 2005 PASCAL Visual Object Classes Challenge. [Citation Graph (0, 0)][DBLP]
    MLCW, 2005, pp:117-176 [Conf]
  11. Moray Allan, Christopher K. I. Williams
    Harmonising Chorales by Probabilistic Inference. [Citation Graph (0, 0)][DBLP]
    NIPS, 2004, pp:- [Conf]
  12. David Barber, Christopher K. I. Williams
    Gaussian Processes for Bayesian Classification via Hybrid Monte Carlo. [Citation Graph (0, 0)][DBLP]
    NIPS, 1996, pp:340-346 [Conf]
  13. Christopher M. Bishop, Markus Svensén, Christopher K. I. Williams
    EM Optimization of Latent-Variables Density Models. [Citation Graph (0, 0)][DBLP]
    NIPS, 1995, pp:465-471 [Conf]
  14. Christopher M. Bishop, Markus Svensén, Christopher K. I. Williams
    GTM: A Principled Alternative to the Self-Organizing Map. [Citation Graph (0, 0)][DBLP]
    NIPS, 1996, pp:354-360 [Conf]
  15. Dan Cornford, Ian T. Nabney, Christopher K. I. Williams
    Adding Constrained Discontinuities to Gaussian Process Models of Wind Fields. [Citation Graph (0, 0)][DBLP]
    NIPS, 1998, pp:861-867 [Conf]
  16. Giancarlo Ferrari-Trecate, Christopher K. I. Williams, Manfred Opper
    Finite-Dimensional Approximation of Gaussian Processes. [Citation Graph (0, 0)][DBLP]
    NIPS, 1998, pp:218-224 [Conf]
  17. Paul W. Goldberg, Christopher K. I. Williams, Christopher M. Bishop
    Regression with Input-dependent Noise: A Gaussian Process Treatment. [Citation Graph (0, 0)][DBLP]
    NIPS, 1997, pp:- [Conf]
  18. Geoffrey E. Hinton, Christopher K. I. Williams, Michael Revow
    Adaptive Elastic Models for Hand-Printed Character Recognition. [Citation Graph (0, 0)][DBLP]
    NIPS, 1991, pp:512-519 [Conf]
  19. John Shawe-Taylor, Christopher K. I. Williams
    The Stability of Kernel Principal Components Analysis and its Relation to the Process Eigenspectrum. [Citation Graph (0, 0)][DBLP]
    NIPS, 2002, pp:367-374 [Conf]
  20. Peter Sollich, Christopher K. I. Williams
    Using the Equivalent Kernel to Understand Gaussian Process Regression. [Citation Graph (0, 0)][DBLP]
    NIPS, 2004, pp:- [Conf]
  21. Francesco Vivarelli, Christopher K. I. Williams
    Discovering Hidden Features with Gaussian Processes Regression. [Citation Graph (0, 0)][DBLP]
    NIPS, 1998, pp:613-619 [Conf]
  22. Max Welling, Felix V. Agakov, Christopher K. I. Williams
    Extreme Components Analysis. [Citation Graph (0, 0)][DBLP]
    NIPS, 2003, pp:- [Conf]
  23. Christopher K. I. Williams
    On a Connection between Kernel PCA and Metric Multidimensional Scaling. [Citation Graph (0, 0)][DBLP]
    NIPS, 2000, pp:675-681 [Conf]
  24. Christopher K. I. Williams
    Computing with Infinite Networks. [Citation Graph (0, 0)][DBLP]
    NIPS, 1996, pp:295-301 [Conf]
  25. Christopher K. I. Williams
    A MCMC Approach to Hierarchical Mixture Modelling. [Citation Graph (0, 0)][DBLP]
    NIPS, 1999, pp:680-686 [Conf]
  26. Christopher K. I. Williams, Nicholas J. Adams
    DTs: Dynamic Trees. [Citation Graph (0, 0)][DBLP]
    NIPS, 1998, pp:634-640 [Conf]
  27. Christopher K. I. Williams, Felix V. Agakov, Stephen N. Felderhof
    Products of Gaussians. [Citation Graph (0, 0)][DBLP]
    NIPS, 2001, pp:1017-1024 [Conf]
  28. Christopher K. I. Williams, John A. Quinn, Neil McIntosh
    Factorial Switching Kalman Filters for Condition Monitoring in Neonatal Intensive Care. [Citation Graph (0, 0)][DBLP]
    NIPS, 2005, pp:- [Conf]
  29. Christopher K. I. Williams, Carl Edward Rasmussen
    Gaussian Processes for Regression. [Citation Graph (0, 0)][DBLP]
    NIPS, 1995, pp:514-520 [Conf]
  30. Christopher K. I. Williams, Michael Revow, Geoffrey E. Hinton
    Using a neural net to instantiate a deformable model. [Citation Graph (0, 0)][DBLP]
    NIPS, 1994, pp:965-972 [Conf]
  31. Christopher K. I. Williams, Matthias Seeger
    Using the Nyström Method to Speed Up Kernel Machines. [Citation Graph (0, 0)][DBLP]
    NIPS, 2000, pp:682-688 [Conf]
  32. Christopher K. I. Williams, Michalis K. Titsias
    Learning About Multiple Objects in Images: Factorial Learning without Factorial Search. [Citation Graph (0, 0)][DBLP]
    NIPS, 2002, pp:1391-1398 [Conf]
  33. Richard S. Zemel, Christopher K. I. Williams, Michael Mozer
    Directional-Unit Boltzmann Machines. [Citation Graph (0, 0)][DBLP]
    NIPS, 1992, pp:172-179 [Conf]
  34. Michalis K. Titsias, Christopher K. I. Williams
    Unsupervised Learning of Multiple Aspects of Moving Objects from Video. [Citation Graph (0, 0)][DBLP]
    Panhellenic Conference on Informatics, 2005, pp:746-756 [Conf]
  35. Miguel Á. Carreira-Perpiñán, Christopher K. I. Williams
    On the Number of Modes of a Gaussian Mixture. [Citation Graph (0, 0)][DBLP]
    Scale-Space, 2003, pp:625-640 [Conf]
  36. Amos J. Storkey, Nigel C. Hambly, Christopher K. I. Williams, Robert G. Mann
    Renewal Strings for Cleaning Astronomical Databases. [Citation Graph (0, 0)][DBLP]
    UAI, 2003, pp:559-566 [Conf]
  37. Jean Ponce, Tamara L. Berg, Mark Everingham, David A. Forsyth, Martial Hebert, Svetlana Lazebnik, Marcin Marszalek, Cordelia Schmid, Bryan C. Russell, A. Torralba, Christopher K. I. Williams, Jianguo Zhang, Andrew Zisserman
    Dataset Issues in Object Recognition. [Citation Graph (0, 0)][DBLP]
    Toward Category-Level Object Recognition, 2006, pp:29-48 [Conf]
  38. Michalis K. Titsias, Christopher K. I. Williams
    Sequential Learning of Layered Models from Video. [Citation Graph (0, 0)][DBLP]
    Toward Category-Level Object Recognition, 2006, pp:577-595 [Conf]
  39. Wolfgang P. Lehrach, Dirk Husmeier, Christopher K. I. Williams
    A regularized discriminative model for the prediction of protein-peptide interactions. [Citation Graph (0, 0)][DBLP]
    Bioinformatics, 2006, v:22, n:5, pp:532-540 [Journal]
  40. Christopher K. I. Williams, Michael Revow, Geoffrey E. Hinton
    Instantiating Deformable Models with a Neural Net. [Citation Graph (0, 0)][DBLP]
    Computer Vision and Image Understanding, 1997, v:68, n:1, pp:120-126 [Journal]
  41. Christopher M. Bishop, Markus Svensén, Christopher K. I. Williams
    Developments of the generative topographic mapping. [Citation Graph (0, 0)][DBLP]
    Neurocomputing, 1998, v:21, n:1-3, pp:203-224 [Journal]
  42. Ian T. Nabney, Dan Cornford, Christopher K. I. Williams
    Bayesian inference for wind field retrieval. [Citation Graph (0, 0)][DBLP]
    Neurocomputing, 2000, v:30, n:1-4, pp:3-11 [Journal]
  43. Nicholas J. Adams, Christopher K. I. Williams
    Dynamic trees for image modelling. [Citation Graph (0, 0)][DBLP]
    Image Vision Comput., 2003, v:21, n:10, pp:865-877 [Journal]
  44. Christopher K. I. Williams
    On a Connection between Kernel PCA and Metric Multidimensional Scaling. [Citation Graph (0, 0)][DBLP]
    Machine Learning, 2002, v:46, n:1-3, pp:11-19 [Journal]
  45. Christopher K. I. Williams, Francesco Vivarelli
    Upper and Lower Bounds on the Learning Curve for Gaussian Processes. [Citation Graph (0, 0)][DBLP]
    Machine Learning, 2000, v:40, n:1, pp:77-102 [Journal]
  46. Christopher M. Bishop, Markus Svensén, Christopher K. I. Williams
    GTM: The Generative Topographic Mapping. [Citation Graph (0, 0)][DBLP]
    Neural Computation, 1998, v:10, n:1, pp:215-234 [Journal]
  47. Christopher K. I. Williams
    How to Pretend That Correlated Variables Are Independent by Using Difference Observations. [Citation Graph (0, 0)][DBLP]
    Neural Computation, 2005, v:17, n:1, pp:1-6 [Journal]
  48. Christopher K. I. Williams
    Computation with Infinite Neural Networks. [Citation Graph (0, 0)][DBLP]
    Neural Computation, 1998, v:10, n:5, pp:1203-1216 [Journal]
  49. Christopher K. I. Williams, Felix V. Agakov
    Products of Gaussians and Probabilistic Minor Component Analysis. [Citation Graph (0, 0)][DBLP]
    Neural Computation, 2002, v:14, n:5, pp:1169-1182 [Journal]
  50. Christopher K. I. Williams, Michalis K. Titsias
    Greedy Learning of Multiple Objects in Images Using Robust Statistics and Factorial Learning. [Citation Graph (0, 0)][DBLP]
    Neural Computation, 2004, v:16, n:5, pp:1039-1062 [Journal]
  51. Francesco Vivarelli, Christopher K. I. Williams
    Comparing Bayesian neural network algorithms for classifying segmented outdoor images. [Citation Graph (0, 0)][DBLP]
    Neural Networks, 2001, v:14, n:4-5, pp:427-437 [Journal]
  52. Richard S. Zemel, Christopher K. I. Williams, Michael Mozer
    Lending direction to neural networks. [Citation Graph (0, 0)][DBLP]
    Neural Networks, 1995, v:8, n:4, pp:503-512 [Journal]
  53. Xiaojuan Feng, Christopher K. I. Williams, Stephen N. Felderhof
    Combining Belief Networks and Neural Networks for Scene Segmentation. [Citation Graph (0, 0)][DBLP]
    IEEE Trans. Pattern Anal. Mach. Intell., 2002, v:24, n:4, pp:467-483 [Journal]
  54. Michael Revow, Christopher K. I. Williams, Geoffrey E. Hinton
    Using Generative Models for Handwritten Digit Recognition. [Citation Graph (0, 0)][DBLP]
    IEEE Trans. Pattern Anal. Mach. Intell., 1996, v:18, n:6, pp:592-606 [Journal]
  55. Amos J. Storkey, Christopher K. I. Williams
    Image Modeling with Position-Encoding Dynamic Trees. [Citation Graph (0, 0)][DBLP]
    IEEE Trans. Pattern Anal. Mach. Intell., 2003, v:25, n:7, pp:859-871 [Journal]
  56. Christopher K. I. Williams, David Barber
    Bayesian Classification With Gaussian Processes. [Citation Graph (0, 0)][DBLP]
    IEEE Trans. Pattern Anal. Mach. Intell., 1998, v:20, n:12, pp:1342-1351 [Journal]
  57. John Shawe-Taylor, Christopher K. I. Williams, Nello Cristianini, Jaz S. Kandola
    On the eigenspectrum of the gram matrix and the generalization error of kernel-PCA. [Citation Graph (0, 0)][DBLP]
    IEEE Transactions on Information Theory, 2005, v:51, n:7, pp:2510-2522 [Journal]
  58. John A. Quinn, Christopher K. I. Williams
    Known Unknowns: Novelty Detection in Condition Monitoring. [Citation Graph (0, 0)][DBLP]
    IbPRIA (1), 2007, pp:1-6 [Conf]
  59. Wolfgang P. Lehrach, Dirk Husmeier, Christopher K. I. Williams
    Probabilistic in Silico Prediction of Protein-Peptide Interactions. [Citation Graph (0, 0)][DBLP]
    Systems Biology and Regulatory Genomics, 2005, pp:188-197 [Conf]

  60. Multi-task Gaussian Process Prediction. [Citation Graph (, )][DBLP]


  61. Multi-task Gaussian Process Learning of Robot Inverse Dynamics. [Citation Graph (, )][DBLP]


  62. Signal masking in Gaussian channels. [Citation Graph (, )][DBLP]


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