David J. C. MacKay

According to our database, David J. C. MacKay authored at least 56 papers between 1990 and 2019.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2019

Ticker: An Adaptive Single-Switch Text Entry Method for Visually Impaired Users.

Emli-Mari Nel, Per Ola Kristensson, David J. C. MacKay

IEEE Trans. Pattern Anal. Mach. Intell., 2019

2018

The Statistical Model for Ticker, an Adaptive Single-Switch Text-Entry Method for Visually Impaired Users.

Emli-Mari Nel, Per Ola Kristensson, David J. C. MacKay

CoRR, 2018

2017

Modelling Noise-Resilient Single-Switch Scanning Systems.

Emli-Mari Nel, Per Ola Kristensson, David J. C. MacKay

CoRR, 2017

2015

Improving PPM with Dynamic Parameter Updates.

Christian Steinruecken, Zoubin Ghahramani, David J. C. MacKay

Proceedings of the 2015 Data Compression Conference, 2015

2014

Speech dasher: a demonstration of text input using speech and approximate pointing.

Keith Vertanen, David J. C. MacKay

Proceedings of the 16th international ACM SIGACCESS conference on Computers & accessibility, 2014

2010

Elliptical slice sampling.

Iain Murray, Ryan Prescott Adams, David J. C. MacKay

Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, 2010

Speech dasher: fast writing using speech and gaze.

Keith Vertanen, David J. C. MacKay

Proceedings of the 28th International Conference on Human Factors in Computing Systems, 2010

2009

Fast and flexible selection with a single switch

Tamara Broderick, David John Cameron MacKay

CoRR, 2009

Predicting and understanding the stability of G-quadruplexes.

Oliver Stegle, Linda Payet, Jean-Louis Mergny, David J. C. MacKay, Julian Leon Huppert

Bioinform., 2009

Tractable nonparametric Bayesian inference in Poisson processes with Gaussian process intensities.

Ryan Prescott Adams, Iain Murray, David J. C. MacKay

Proceedings of the 26th Annual International Conference on Machine Learning, 2009

2008

Gaussian Process Robust Regression for Noisy Heart Rate Data.

Oliver Stegle, Sebastian V. Fallert, David J. C. MacKay, Søren Brage

IEEE Trans. Biomed. Eng., 2008

The Gaussian Process Density Sampler.

Ryan Prescott Adams, Iain Murray, David J. C. MacKay

Proceedings of the Advances in Neural Information Processing Systems 21, 2008

2006

MCMC for Doubly-intractable Distributions.

Iain Murray, Zoubin Ghahramani, David J. C. MacKay

Proceedings of the UAI '06, 2006

2005

Nested sampling for Potts models.

Iain Murray, David J. C. MacKay, Zoubin Ghahramani, John Skilling

Proceedings of the Advances in Neural Information Processing Systems 18 [Neural Information Processing Systems, 2005

2004

Sparse-graph codes for quantum error correction.

David J. C. MacKay, G. Mitchison, P. L. McFadden

IEEE Trans. Inf. Theory, 2004

Modelling Uncertainty in the Game of Go.

David H. Stern, Thore Graepel, David J. C. MacKay

Proceedings of the Advances in Neural Information Processing Systems 17 [Neural Information Processing Systems, 2004

Eye tracking off the shelf.

Dan Witzner Hansen, David J. C. MacKay, John Paulin Hansen, Mads Nielsen

Proceedings of the Eye Tracking Research & Application Symposium, 2004

Efficient Communication by Breathing.

Tom Shorrock, David J. C. MacKay, Chris Ball

Proceedings of the Deterministic and Statistical Methods in Machine Learning, 2004

2003

Sparse low-density parity-check codes for channels with cross-talk.

Edward A. Ratzer, David J. C. MacKay

Proceedings of the Proceedings 2003 IEEE Information Theory Workshop, 2003

Information theory, inference, and learning algorithms.

David J. C. MacKay

Cambridge University Press, ISBN: 978-0-521-64298-9, 2003

2002

Dasher: A Gesture-Driven Data Entry Interface for Mobile Computing.

David J. Ward, Alan F. Blackwell, David J. C. MacKay

Hum. Comput. Interact., 2002

Weaknesses of Margulis and Ramanujan-Margulis low-density parity-check cCodes.

David J. C. MacKay, Michael S. Postol

Proceedings of the Second Irish Conference on the Mathematical Foundations of Computer Science and Information Technology, 2002

Performance of low density parity check codes as a function of actual and assumed noise levels.

David J. C. MacKay, Christopher P. Hesketh

Proceedings of the Second Irish Conference on the Mathematical Foundations of Computer Science and Information Technology, 2002

Fast Hands-free Writing by Gaze Direction

David J. Ward, David J. C. MacKay

CoRR, 2002

A decomposition model to track gene expression signatures: preview on observer-independent classification of ovarian cancer.

Ann-Marie Martoglio, James W. Miskin, Stephen K. Smith, David J. C. MacKay

Bioinform., 2002

2001

Errata for "Good error-correcting codes based on very sparse matrices".

David J. C. MacKay

IEEE Trans. Inf. Theory, 2001

Reliable communication over channels with insertions, deletions, and substitutions.

Matthew C. Davey, David J. C. MacKay

IEEE Trans. Inf. Theory, 2001

Model fitting as an aid to bridge balancing in neuronal recording.

Virginia R. de Sa, David J. C. MacKay

Neurocomputing, 2001

Almost-Certainly Runlength-Limiting Codes.

David J. C. MacKay

Proceedings of the Cryptography and Coding, 2001

2000

Variational Gaussian process classifiers.

Mark N. Gibbs, David J. C. MacKay

IEEE Trans. Neural Networks Learn. Syst., 2000

Dasher - a data entry interface using continuous gestures and language models.

David J. Ward, Alan F. Blackwell, David J. C. MacKay

Proceedings of the 13th Annual ACM Symposium on User Interface Software and Technology, 2000

1999

Good Error-Correcting Codes Based on Very Sparse Matrices.

David J. C. MacKay

IEEE Trans. Inf. Theory, 1999

Comparison of constructions of irregular Gallager codes.

David J. C. MacKay, Simon T. Wilson, Matthew C. Davey

IEEE Trans. Commun., 1999

Comparison of Approximate Methods for Handling Hyperparameters.

David J. C. MacKay

Neural Comput., 1999

The Nonnegative Boltzmann Machine.

Oliver B. Downs, David J. C. MacKay, Daniel D. Lee

Proceedings of the Advances in Neural Information Processing Systems 12, [NIPS Conference, Denver, Colorado, USA, November 29, 1999

1998

Interpolation models with multiple hyperparameters.

David J. C. MacKay, Ryo Takeuchi

Stat. Comput., 1998

Choice of Basis for Laplace Approximation.

David J. C. MacKay

Mach. Learn., 1998

Turbo Decoding as an Instance of Pearl's "Belief Propagation" Algorithm.

Robert J. McEliece, David J. C. MacKay, Jung-Fu Cheng

IEEE J. Sel. Areas Commun., 1998

Low-density parity check codes over GF(q).

Matthew C. Davey, David J. C. MacKay

IEEE Commun. Lett., 1998

Introduction to Monte Carlo Methods.

David John Cameron MacKay

Proceedings of the Learning in Graphical Models, 1998

1997

A Revolution: Belief Propagation in Graphs with Cycles.

Brendan J. Frey, David J. C. MacKay

Proceedings of the Advances in Neural Information Processing Systems 10, 1997

1996

Equivalence of Linear Boltzmann Chains and Hidden Markov Models.

David J. C. MacKay

Neural Comput., 1996

1995

A hierarchical Dirichlet language model.

David J. C. MacKay, Linda C. Bauman Peto

Nat. Lang. Eng., 1995

Developments in Probabilistic Modelling with Neural Networks - Ensemble Learning.

David J. C. MacKay

Proceedings of the Neural Networks: Artificial Intelligence and Industrial Applications, 1995

Bayesian Methods for Mixtures of Experts.

Steve R. Waterhouse, David J. C. MacKay, Anthony J. Robinson

Proceedings of the Advances in Neural Information Processing Systems 8, 1995

Good Codes Based on Very Sparse Matrices.

David J. C. MacKay

Proceedings of the Cryptography and Coding, 1995

1994

The Role of Constraints in Hebbian Learning.

Kenneth D. Miller, David J. C. MacKay

Neural Comput., 1994

A Free Energy Minimization Framework for Inference Problems in modulo 2 Arithmetic.

David J. C. MacKay

Proceedings of the Fast Software Encryption: Second International Workshop. Leuven, 1994

1993

Bayesian regularisation methods in a hybrid MLP-HMM system.

Steve Renals, David J. C. MacKay

Proceedings of the Third European Conference on Speech Communication and Technology, 1993

1992

The Evidence Framework Applied to Classification Networks.

David J. C. MacKay

Neural Comput., 1992

Information-Based Objective Functions for Active Data Selection.

David J. C. MacKay

Neural Comput., 1992

A Practical Bayesian Framework for Backpropagation Networks.

David J. C. MacKay

Neural Comput., 1992

Bayesian Interpolation.

David J. C. MacKay

Neural Comput., 1992

1991

Bayesian Model Comparison and Backprop Nets.

David J. C. MacKay

Proceedings of the Advances in Neural Information Processing Systems 4, 1991

Unsupervised Classifiers, Mutual Information and 'Phantom Targets'.

John S. Bridle, Anthony J. R. Heading, David J. C. MacKay

Proceedings of the Advances in Neural Information Processing Systems 4, 1991

1990

Analysis of Linsker's Simulations of Hebbian Rules.

David J. C. MacKay, Kenneth D. Miller

Neural Comput., 1990