Christopher K. I. Williams

ORCID

Publication Activity (10 Years)

Years Active: 1991-2024
Publications (10 Years): 56

Top Venues

Publications

Christopher K. I. Williams
Naive Bayes Classifiers and One-hot Encoding of Categorical Variables. CoRR (2024)
Alfredo Nazábal, Nikolaos Tsagkas, Christopher K. I. Williams
Inference and Learning for Generative Capsule Models. Neural Comput. 35 (4) (2023)
Hector Zenil, Jesper Tegnér, Felipe S. Abrahão, Alexander Lavin, Vipin Kumar, Jeremy G. Frey, Adrian Weller, Larisa N. Soldatova, Alan R. Bundy, Nicholas R. Jennings, Koichi Takahashi, Lawrence Hunter, Saso Dzeroski, Andrew Briggs, Frederick D. Gregory, Carla P. Gomes, Christopher K. I. Williams, Jon Rowe, James A. Evans, Hiroaki Kitano, Joshua B. Tenenbaum, Ross D. King
The Future of Fundamental Science Led by Generative Closed-Loop Artificial Intelligence. CoRR (2023)
Tomas Petricek, Gerrit J. J. van den Burg, Alfredo Nazábal, Taha Ceritli, Ernesto Jiménez-Ruiz, Christopher K. I. Williams
AI Assistants: A Framework for Semi-Automated Data Wrangling. IEEE Trans. Knowl. Data Eng. 35 (9) (2023)
Michael P. J. Camilleri, Li Zhang, Rasneer S. Bains, Andrew Zisserman, Christopher K. I. Williams
Persistent animal identification leveraging non-visual markers. Mach. Vis. Appl. 34 (4) (2023)
Michael P. J. Camilleri, Rasneer S. Bains, Christopher K. I. Williams
Of Mice and Mates: Automated Classification and Modelling of Mouse Behaviour in Groups using a Single Model across Cages. CoRR (2023)
Christopher K. I. Williams
Structured Generative Models for Scene Understanding. CoRR (2023)
Christopher K. I. Williams
On Suspicious Coincidences and Pointwise Mutual Information. CoRR (2022)
Christopher K. I. Williams
On Suspicious Coincidences and Pointwise Mutual Information. Neural Comput. 34 (10) (2022)
Tijl De Bie, Luc De Raedt, José Hernández-Orallo, Holger H. Hoos, Padhraic Smyth, Christopher K. I. Williams
Automating data science. Commun. ACM 65 (3) (2022)
Tomas Petricek, Gerrit J. J. van den Burg, Alfredo Nazábal, Taha Ceritli, Ernesto Jiménez-Ruiz, Christopher K. I. Williams
AI Assistants: A Framework for Semi-Automated Data Wrangling. CoRR (2022)
Alex Bird, Christopher K. I. Williams, Christopher Hawthorne
Multi-Task Dynamical Systems. CoRR (2022)
Cian Eastwood, Ian Mason, Christopher K. I. Williams, Bernhard Schölkopf
Source-Free Adaptation to Measurement Shift via Bottom-Up Feature Restoration. ICLR (2022)
Christopher K. I. Williams
The Elliptical Quartic Exponential Distribution: An Annular Distribution Obtained via Maximum Entropy. CoRR (2022)
Cian Eastwood, Nanbo Li, Christopher K. I. Williams
Align-Deform-Subtract: An Interventional Framework for Explaining Object Differences. CoRR (2022)
Alex Bird, Christopher K. I. Williams, Christopher Hawthorne
Multi-Task Dynamical Systems. J. Mach. Learn. Res. 23 (2022)
Alfredo Nazábal, Nikolaos Tsagkas, Christopher K. I. Williams
Inference and Learning for Generative Capsule Models. CoRR (2022)
Tijl De Bie, Luc De Raedt, José Hernández-Orallo, Holger H. Hoos, Padhraic Smyth, Christopher K. I. Williams
Automating Data Science: Prospects and Challenges. CoRR (2021)
Taha Ceritli, Christopher K. I. Williams
ptype-cat: Inferring the Type and Values of Categorical Variables. CoRR (2021)
Christopher K. I. Williams
The Effect of Class Imbalance on Precision-Recall Curves. Neural Comput. 33 (4) (2021)
Taha Ceritli, Christopher K. I. Williams
Identifying the Units of Measurement in Tabular Data. CoRR (2021)
Cian Eastwood, Ian Mason, Christopher K. I. Williams
Unit-level surprise in neural networks. ICBINB@NeurIPS (2021)
Gerrit J. J. van den Burg, Christopher K. I. Williams
On Memorization in Probabilistic Deep Generative Models. CoRR (2021)
Cian Eastwood, Ian Mason, Christopher K. I. Williams, Bernhard Schölkopf
Source-Free Adaptation to Measurement Shift via Bottom-Up Feature Restoration. CoRR (2021)
Alfredo Nazábal, Christopher K. I. Williams
Inference for Generative Capsule Models. CoRR (2021)
Michael P. J. Camilleri, Li Zhang, Rasneer S. Bains, Andrew Zisserman, Christopher K. I. Williams
Tracking and Long-Term Identification Using Non-Visual Markers. CoRR (2021)
Lukasz Romaszko, Christopher K. I. Williams, John M. Winn
Learning Direct Optimization for scene understanding. Pattern Recognit. 105 (2020)
Alfredo Nazábal, Christopher K. I. Williams, Giovanni Colavizza, Camila Rangel Smith, Angus Williams
Data Engineering for Data Analytics: A Classification of the Issues, and Case Studies. CoRR (2020)
Christopher K. I. Williams
The Effect of Class Imbalance on Precision-Recall Curves. CoRR (2020)
Simão Eduardo, Alfredo Nazábal, Christopher K. I. Williams, Charles Sutton
Robust Variational Autoencoders for Outlier Detection and Repair of Mixed-Type Data. AISTATS (2020)
Mark Collier, Alfredo Nazábal, Christopher K. I. Williams
VAEs in the Presence of Missing Data. CoRR (2020)
Gerrit J. J. van den Burg, Christopher K. I. Williams
An Evaluation of Change Point Detection Algorithms. CoRR (2020)
Taha Ceritli, Christopher K. I. Williams, James Geddes
ptype: probabilistic type inference. Data Min. Knowl. Discov. 34 (3) (2020)
Alex Bird, Christopher K. I. Williams
Customizing Sequence Generation with Multi-Task Dynamical Systems. CoRR (2019)
Michael P. J. Camilleri, Christopher K. I. Williams
The Extended Dawid-Skene Model: Fusing Information from Multiple Data Schemas. CoRR (2019)
Simão Eduardo, Alfredo Nazábal, Christopher K. I. Williams, Charles Sutton
Robust Variational Autoencoders for Outlier Detection in Mixed-Type Data. CoRR (2019)
Charlie Nash, Nate Kushman, Christopher K. I. Williams
Inverting Supervised Representations with Autoregressive Neural Density Models. AISTATS (2019)
Alex Bird, Christopher K. I. Williams, Christopher Hawthorne
Multi-Task Time Series Analysis applied to Drug Response Modelling. AISTATS (2019)
Taha Ceritli, Christopher K. I. Williams, James Geddes
ptype: Probabilistic Type Inference. CoRR (2019)
Alex Bird, Christopher K. I. Williams, Christopher Hawthorne
Multi-Task Time Series Analysis applied to Drug Response Modelling. CoRR (2019)
Charlie Nash, Nate Kushman, Christopher K. I. Williams
Inverting Supervised Representations with Autoregressive Neural Density Models. CoRR (2018)
Sohan Seth, Ahsan R. Akram, Kevin Dhaliwal, Christopher K. I. Williams
Estimating Bacterial and Cellular Load in FCFM Imaging. J. Imaging 4 (1) (2018)
Lukasz Romaszko, Christopher K. I. Williams, John M. Winn
Learning Direct Optimization for Scene Understanding. CoRR (2018)
Cian Eastwood, Christopher K. I. Williams
A Framework for the Quantitative Evaluation of Disentangled Representations. ICLR (Poster) (2018)
Christopher K. I. Williams, Charlie Nash
Autoencoders and Probabilistic Inference with Missing Data: An Exact Solution for The Factor Analysis Case. CoRR (2018)
Sohan Seth, Ahsan R. Akram, Kevin Dhaliwal, Christopher K. I. Williams
Estimating Bacterial Load in FCFM Imaging. MIUA (2017)
Charlie Nash, Christopher K. I. Williams
The shape variational autoencoder: A deep generative model of part-segmented 3D objects. Comput. Graph. Forum 36 (5) (2017)
Lukasz Romaszko, Christopher K. I. Williams, Pol Moreno, Pushmeet Kohli
Vision-as-Inverse-Graphics: Obtaining a Rich 3D Explanation of a Scene from a Single Image. ICCV Workshops (2017)
Pol Moreno, Christopher K. I. Williams, Charlie Nash, Pushmeet Kohli
Overcoming Occlusion with Inverse Graphics. ECCV Workshops (3) (2016)
Konstantinos Georgatzis, Christopher K. I. Williams, Christopher Hawthorne
Input-Output Non-Linear Dynamical Systems applied to Physiological Condition Monitoring. CoRR (2016)
Konstantinos Georgatzis, Christopher K. I. Williams, Christopher Hawthorne
Input-Output Non-Linear Dynamical Systems applied to Physiological Condition Monitoring. MLHC (2016)
Adam McCarthy, Christopher K. I. Williams
Predicting Patient State-of-Health using Sliding Window and Recurrent Classifiers. CoRR (2016)
Shell Xu Hu, Christopher K. I. Williams, Sinisa Todorovic
Tree-Cut for Probabilistic Image Segmentation. CoRR (2015)
Konstantinos Georgatzis, Christopher K. I. Williams
Discriminative Switching Linear Dynamical Systems applied to Physiological Condition Monitoring. CoRR (2015)
Konstantinos Georgatzis, Christopher K. I. Williams
Discriminative Switching Linear Dynamical Systems applied to Physiological Condition Monitoring. UAI (2015)
Mark Everingham, S. M. Ali Eslami, Luc Van Gool, Christopher K. I. Williams, John M. Winn, Andrew Zisserman
The Pascal Visual Object Classes Challenge: A Retrospective. Int. J. Comput. Vis. 111 (1) (2015)
Jyri J. Kivinen, Christopher K. I. Williams, Nicolas Heess
Visual Boundary Prediction: A Deep Neural Prediction Network and Quality Dissection. AISTATS (2014)
S. M. Ali Eslami, Nicolas Heess, Christopher K. I. Williams, John M. Winn
The Shape Boltzmann Machine: A Strong Model of Object Shape. Int. J. Comput. Vis. 107 (2) (2014)
Ioan Stanculescu, Christopher K. I. Williams, Yvonne Freer
A Hierarchical Switching Linear Dynamical System Applied to the Detection of Sepsis in Neonatal Condition Monitoring. UAI (2014)
Ioan Stanculescu, Christopher K. I. Williams, Yvonne Freer
Autoregressive Hidden Markov Models for the Early Detection of Neonatal Sepsis. IEEE J. Biomed. Health Informatics 18 (5) (2014)
Amos J. Storkey, Nigel C. Hambly, Christopher K. I. Williams, Robert G. Mann
Renewal Strings for Cleaning Astronomical Databases. CoRR (2014)
Krzysztof Chalupka, Christopher K. I. Williams, Iain Murray
A framework for evaluating approximation methods for Gaussian process regression. J. Mach. Learn. Res. 14 (1) (2013)
Krzysztof Chalupka, Christopher K. I. Williams, Iain Murray
A Framework for Evaluating Approximation Methods for Gaussian Process Regression CoRR (2012)
S. M. Ali Eslami, Christopher K. I. Williams
A Generative Model for Parts-based Object Segmentation. NIPS (2012)
Andrew Zisserman, John M. Winn, Andrew W. Fitzgibbon, Luc Van Gool, Josef Sivic, Christopher K. I. Williams, David C. Hogg
In Memoriam: Mark Everingham. IEEE Trans. Pattern Anal. Mach. Intell. 34 (11) (2012)
Jyri J. Kivinen, Christopher K. I. Williams
Multiple Texture Boltzmann Machines. AISTATS (2012)
Bill Triggs, Christopher K. I. Williams
Special Issue on Probabilistic Models for Image Understanding, Part II. Int. J. Comput. Vis. 95 (3) (2011)
Seyed Mohammadali Eslami, Christopher K. I. Williams
Factored Shapes and Appearances for Parts-based Object Understanding. BMVC (2011)
Christopher K. I. Williams, Ioan Stanculescu
Automating the Calibration of a Neonatal Condition Monitoring System. AIME (2011)
Grigori Fursin, Yuriy Kashnikov, Abdul Wahid Memon, Zbigniew Chamski, Olivier Temam, Mircea Namolaru, Elad Yom-Tov, Bilha Mendelson, Ayal Zaks, Eric Courtois, François Bodin, Phil Barnard, Elton Ashton, Edwin V. Bonilla, John Thomson, Christopher K. I. Williams, Michael F. P. O'Boyle
Milepost GCC: Machine Learning Enabled Self-tuning Compiler. Int. J. Parallel Program. 39 (3) (2011)
Jyri J. Kivinen, Christopher K. I. Williams
Transformation Equivariant Boltzmann Machines. ICANN (1) (2011)
Stefan Harmeling, Christopher K. I. Williams
Greedy Learning of Binary Latent Trees. IEEE Trans. Pattern Anal. Mach. Intell. 33 (6) (2011)
Bill Triggs, Christopher K. I. Williams
Editorial: Special Issue on Probabilistic Models for Image Understanding. Int. J. Comput. Vis. 88 (2) (2010)
Mark Everingham, Luc Van Gool, Christopher K. I. Williams, John M. Winn, Andrew Zisserman
The Pascal Visual Object Classes (VOC) Challenge. Int. J. Comput. Vis. 88 (2) (2010)
John A. Quinn, Christopher K. I. Williams, Neil McIntosh
Factorial Switching Linear Dynamical Systems Applied to Physiological Condition Monitoring. IEEE Trans. Pattern Anal. Mach. Intell. 31 (9) (2009)
Nicolas Heess, Christopher K. I. Williams, Geoffrey E. Hinton
Learning Generative Texture Models with extended Fields-of-Experts. BMVC (2009)
Moray Allan, Christopher K. I. Williams
Object localisation using the Generative Template of Features. Comput. Vis. Image Underst. 113 (7) (2009)
John A. Quinn, Christopher K. I. Williams
Signal masking in Gaussian channels. ICASSP (2008)
Kian Ming Adam Chai, Christopher K. I. Williams, Stefan Klanke, Sethu Vijayakumar
Multi-task Gaussian Process Learning of Robot Inverse Dynamics. NIPS (2008)
John A. Quinn, Christopher K. I. Williams
Known Unknowns: Novelty Detection in Condition Monitoring. IbPRIA (1) (2007)
Edwin V. Bonilla, Kian Ming Adam Chai, Christopher K. I. Williams
Multi-task Gaussian Process Prediction. NIPS (2007)
Edwin V. Bonilla, Felix V. Agakov, Christopher K. I. Williams
Kernel Multi-task Learning using Task-specific Features. AISTATS (2007)
Edwin V. Bonilla, Christopher K. I. Williams, Felix V. Agakov, John Cavazos, John Thomson, Michael F. P. O'Boyle
Predictive search distributions. ICML (2006)
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. CGO (2006)
Jean Ponce, Tamara L. Berg, Mark Everingham, David A. Forsyth, Martial Hebert, Svetlana Lazebnik, Marcin Marszalek, Cordelia Schmid, Bryan C. Russell, Antonio Torralba, Christopher K. I. Williams, Jianguo Zhang, Andrew Zisserman
Dataset Issues in Object Recognition. Toward Category-Level Object Recognition (2006)
Michalis K. Titsias, Christopher K. I. Williams
Sequential Learning of Layered Models from Video. Toward Category-Level Object Recognition (2006)
Wolfgang P. Lehrach, Dirk Husmeier, Christopher K. I. Williams
A regularized discriminative model for the prediction of protein-peptide interactions. Bioinform. 22 (5) (2006)
Christopher K. I. Williams
How to Pretend That Correlated Variables Are Independent by Using Difference Observations. Neural Comput. 17 (1) (2005)
Wolfgang P. Lehrach, Dirk Husmeier, Christopher K. I. Williams
Prediction of Protein-Peptide Interactions. Systems Biology and Regulatory Genomics (2005)
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. IEEE Trans. Inf. Theory 51 (7) (2005)
Michalis K. Titsias, Christopher K. I. Williams
Unsupervised Learning of Multiple Aspects of Moving Objects from Video. Panhellenic Conference on Informatics (2005)
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, Thomas L. 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. MLCW (2005)
Christopher K. I. Williams, John A. Quinn, Neil McIntosh
Factorial Switching Kalman Filters for Condition Monitoring in Neonatal Intensive Care. NIPS (2005)
Moray Allan, Michalis K. Titsias, Christopher K. I. Williams
Fast Learning of Sprites using Invariant Features. BMVC (2005)
Christopher K. I. Williams, Michalis K. Titsias
Greedy Learning of Multiple Objects in Images Using Robust Statistics and Factorial Learning. Neural Comput. 16 (5) (2004)
Peter Sollich, Christopher K. I. Williams
Understanding Gaussian Process Regression Using the Equivalent Kernel. Deterministic and Statistical Methods in Machine Learning (2004)
Moray Allan, Christopher K. I. Williams
Harmonising Chorales by Probabilistic Inference. NIPS (2004)
Michalis K. Titsias, Christopher K. I. Williams
Fast Unsupervised Greedy Learning of Multiple Objects and Parts from Video. CVPR Workshops (2004)
Peter Sollich, Christopher K. I. Williams
Using the Equivalent Kernel to Understand Gaussian Process Regression. NIPS (2004)
Nicholas J. Adams, Christopher K. I. Williams
Dynamic trees for image modelling. Image Vis. Comput. 21 (10) (2003)

Christopher K. I. Williams.css-eqlu8i{font-size:small;padding-left:4px;}

Publication Activity (10 Years)

Top Topics

Top Venues

Christopher K. I. Williams