Williams, Christopher K.I.

47 publications

NeurIPS 2023 A Unified Framework for U-Net Design and Analysis Christopher K. I. Williams, Fabian Falck, George Deligiannidis, Chris C Holmes, Arnaud Doucet, Saifuddin Syed

NeurIPS 2022 A Multi-Resolution Framework for U-Nets with Applications to Hierarchical VAEs Fabian Falck, Christopher K. I. Williams, Dominic Danks, George Deligiannidis, Christopher Yau, Chris C Holmes, Arnaud Doucet, Matthew Willetts

JMLR 2022 Multi-Task Dynamical Systems Alex Bird, Christopher K. I. Williams, Christopher Hawthorne

AISTATS 2020 Robust Variational Autoencoders for Outlier Detection and Repair of Mixed-Type Data Simao Eduardo, Alfredo Nazabal, Christopher K. I. Williams, Charles Sutton

AISTATS 2019 Inverting Supervised Representations with Autoregressive Neural Density Models Charlie Nash, Nate Kushman, Christopher K.I. Williams

ICLR 2018 A Framework for the Quantitative Evaluation of Disentangled Representations Cian Eastwood, Christopher K. I. Williams

ICCVW 2017 Vision-as-Inverse-Graphics: Obtaining a Rich 3D Explanation of a Scene from a Single Image Lukasz Romaszko, Christopher K. I. Williams, Pol Moreno, Pushmeet Kohli

ECCV 2016 Overcoming Occlusion with Inverse Graphics Pol Moreno, Christopher K. I. Williams, Charlie Nash, Pushmeet Kohli

ECCVW 2016 Overcoming Occlusion with Inverse Graphics Pol Moreno, Christopher K. I. Williams, Charlie Nash, Pushmeet Kohli

UAI 2015 Discriminative Switching Linear Dynamical Systems Applied to Physiological Condition Monitoring Konstantinos Georgatzis, Christopher K. I. Williams

UAI 2014 A Hierarchical Switching Linear Dynamical System Applied to the Detection of Sepsis in Neonatal Condition Monitoring Ioan Stanculescu, Christopher K. I. Williams, Yvonne Freer

AISTATS 2014 Visual Boundary Prediction: A Deep Neural Prediction Network and Quality Dissection Jyri J. Kivinen, Christopher K. I. Williams, Nicolas Heess

JMLR 2013 A Framework for Evaluating Approximation Methods for Gaussian Process Regression Krzysztof Chalupka, Christopher K. I. Williams, Iain Murray

AISTATS 2007 Kernel Multi-Task Learning Using Task-Specific Features Edwin V. Bonilla, Felix V. Agakov, Christopher K. I. Williams

ICML 2006 Predictive Search Distributions Edwin V. Bonilla, Christopher K. I. Williams, Felix V. Agakov, John Cavazos, John Thomson, Michael F. P. O'Boyle

CVPR 2004 Fast Unsupervised Greedy Learning of Multiple Objects and Parts from Video Michalis K. Titsias, Christopher K. I. Williams

CVPRW 2004 Fast Unsupervised Greedy Learning of Multiple Objects and Parts from Video Michalis K. Titsias, Christopher K. I. Williams

NeCo 2004 Greedy Learning of Multiple Objects in Images Using Robust Statistics and Factorial Learning Christopher K. I. Williams, Michalis K. Titsias

AISTATS 2003 Fast Forward Selection to Speed up Sparse Gaussian Process Regression Matthias W. Seeger, Christopher K. I. Williams, Neil D. Lawrence

UAI 2003 Renewal Strings for Cleaning Astronomical Databases Amos J. Storkey, Nigel C. Hambly, Christopher K. I. Williams, Robert G. Mann

ECCV 2002 Dynamic Trees: Learning to Model Outdoor Scenes Nicholas J. Adams, Christopher K. I. Williams

NeurIPS 2002 Learning About Multiple Objects in Images: Factorial Learning Without Factorial Search Christopher K. I. Williams, Michalis K. Titsias

MLJ 2002 On a Connection Between Kernel PCA and Metric Multidimensional Scaling Christopher K. I. Williams

ALT 2002 On the Eigenspectrum of the Gram Matrix and Its Relationship to the Operator Eigenspectrum John Shawe-Taylor, Christopher K. I. Williams, Nello Cristianini, Jaz S. Kandola

NeCo 2002 Products of Gaussians and Probabilistic Minor Component Analysis Christopher K. I. Williams, Felix V. Agakov

AISTATS 2001 Dynamic Positional Trees for Structural Image Analysis Amos J. Storkey, Christopher K. I. Williams

NeurIPS 2000 On a Connection Between Kernel PCA and Metric Multidimensional Scaling Christopher K. I. Williams

ICML 2000 The Effect of the Input Density Distribution on Kernel-Based Classifiers Christopher K. I. Williams, Matthias W. Seeger

MLJ 2000 Upper and Lower Bounds on the Learning Curve for Gaussian Processes Christopher K. I. Williams, Francesco Vivarelli

NeurIPS 2000 Using the Nyström Method to Speed up Kernel Machines Christopher K. I. Williams, Matthias Seeger

NeurIPS 1999 A MCMC Approach to Hierarchical Mixture Modelling Christopher K. I. Williams

NeurIPS 1998 Adding Constrained Discontinuities to Gaussian Process Models of Wind Fields Dan Cornford, Ian T. Nabney, Christopher K. I. Williams

NeCo 1998 Computation with Infinite Neural Networks Christopher K. I. Williams

NeurIPS 1998 DTs: Dynamic Trees Christopher K. I. Williams, Nicholas J. Adams

NeurIPS 1998 Discovering Hidden Features with Gaussian Processes Regression Francesco Vivarelli, Christopher K. I. Williams

NeurIPS 1998 Finite-Dimensional Approximation of Gaussian Processes Giancarlo Ferrari-Trecate, Christopher K. I. Williams, Manfred Opper

NeCo 1998 GTM: The Generative Topographic Mapping Christopher M. Bishop, Markus Svensén, Christopher K. I. Williams

NeurIPS 1997 Regression with Input-Dependent Noise: A Gaussian Process Treatment Paul W. Goldberg, Christopher K. I. Williams, Christopher M. Bishop

NeurIPS 1996 Computing with Infinite Networks Christopher K. I. Williams

NeurIPS 1996 GTM: A Principled Alternative to the Self-Organizing mAP Christopher M. Bishop, Markus Svensén, Christopher K. I. Williams

NeurIPS 1996 Gaussian Processes for Bayesian Classification via Hybrid Monte Carlo David Barber, Christopher K. I. Williams

NeurIPS 1995 EM Optimization of Latent-Variable Density Models Christopher M. Bishop, Markus Svensén, Christopher K. I. Williams

NeurIPS 1995 Gaussian Processes for Regression Christopher K. I. Williams, Carl Edward Rasmussen

NeurIPS 1994 Using a Neural Net to Instantiate a Deformable Model Christopher K. I. Williams, Michael Revow, Geoffrey E. Hinton

NeurIPS 1992 Directional-Unit Boltzmann Machines Richard S. Zemel, Christopher K. I. Williams, Michael Mozer

NeCo 1992 Learning to Segment Images Using Dynamic Feature Binding Michael C. Mozer, Richard S. Zemel, Marlene Behrmann, Christopher K. I. Williams

NeurIPS 1991 Adaptive Elastic Models for Hand-Printed Character Recognition Geoffrey E. Hinton, Christopher K. I. Williams, Michael D. Revow