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David J. C. MacKay
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2010 – 2019
- 2019
- [j25]Emli-Mari Nel
, Per Ola Kristensson, David J. C. MacKay:
Ticker: An Adaptive Single-Switch Text Entry Method for Visually Impaired Users. IEEE Trans. Pattern Anal. Mach. Intell. 41(11): 2756-2769 (2019) - 2018
- [i4]Emli-Mari Nel, Per Ola Kristensson, David J. C. MacKay:
The Statistical Model for Ticker, an Adaptive Single-Switch Text-Entry Method for Visually Impaired Users. CoRR abs/1804.07777 (2018) - 2017
- [i3]Emli-Mari Nel, Per Ola Kristensson, David J. C. MacKay:
Modelling Noise-Resilient Single-Switch Scanning Systems. CoRR abs/1712.10073 (2017) - 2015
- [c26]Christian Steinruecken, Zoubin Ghahramani, David J. C. MacKay:
Improving PPM with Dynamic Parameter Updates. DCC 2015: 193-202 - 2014
- [c25]Keith Vertanen, David J. C. MacKay:
Speech dasher: a demonstration of text input using speech and approximate pointing. ASSETS 2014: 353-354 - 2010
- [c24]Keith Vertanen, David J. C. MacKay:
Speech dasher: fast writing using speech and gaze. CHI 2010: 595-598 - [c23]Iain Murray, Ryan Prescott Adams, David J. C. MacKay:
Elliptical slice sampling. AISTATS 2010: 541-548
2000 – 2009
- 2009
- [j24]Oliver Stegle
Predicting and understanding the stability of G-quadruplexes. Bioinform. 25(12) (2009) - [c22]Ryan Prescott Adams, Iain Murray, David J. C. MacKay:
Tractable nonparametric Bayesian inference in Poisson processes with Gaussian process intensities. ICML 2009: 9-16 - [i2]Tamara Broderick, David John Cameron MacKay:
Fast and flexible selection with a single switch. CoRR abs/0909.2450 (2009) - 2008
- [j23]Oliver Stegle
Gaussian Process Robust Regression for Noisy Heart Rate Data. IEEE Trans. Biomed. Eng. 55(9): 2143-2151 (2008) - [c21]Ryan Prescott Adams, Iain Murray, David J. C. MacKay:
The Gaussian Process Density Sampler. NIPS 2008: 9-16 - 2006
- [c20]Iain Murray, Zoubin Ghahramani, David J. C. MacKay:
MCMC for Doubly-intractable Distributions. UAI 2006 - 2005
- [c19]Iain Murray, David J. C. MacKay, Zoubin Ghahramani, John Skilling:
Nested sampling for Potts models. NIPS 2005: 947-954 - 2004
- [j22]David J. C. MacKay, G. Mitchison, P. L. McFadden:
Sparse-graph codes for quantum error correction. IEEE Trans. Inf. Theory 50(10): 2315-2330 (2004) - [c18]Tom Shorrock, David J. C. MacKay, Chris Ball:
Efficient Communication by Breathing. Deterministic and Statistical Methods in Machine Learning 2004: 88-97 - [c17]Dan Witzner Hansen, David J. C. MacKay, John Paulin Hansen, Mads Nielsen:
Eye tracking off the shelf. ETRA 2004: 58 - [c16]David H. Stern, Thore Graepel, David J. C. MacKay:
Modelling Uncertainty in the Game of Go. NIPS 2004: 1353-1360 - 2003
- [b1]David J. C. MacKay:
Information theory, inference, and learning algorithms. Cambridge University Press 2003, ISBN 978-0-521-64298-9, pp. I-XII, 1-628 - [c15]Edward A. Ratzer, David J. C. MacKay:
Sparse low-density parity-check codes for channels with cross-talk. ITW 2003: 127-130 - 2002
- [j21]Ann-Marie Martoglio, James W. Miskin, Stephen K. Smith
A decomposition model to track gene expression signatures: preview on observer-independent classification of ovarian cancer. Bioinform. 18(12): 1617-1624 (2002) - [j20]David J. Ward, Alan F. Blackwell, David J. C. MacKay:
Dasher: A Gesture-Driven Data Entry Interface for Mobile Computing. Hum. Comput. Interact. 17(2-3): 199-228 (2002) - [c14]David J. C. MacKay, Christopher P. Hesketh:
Performance of low density parity check codes as a function of actual and assumed noise levels. MFCSIT 2002: 89-96 - [c13]David J. C. MacKay, Michael S. Postol:
Weaknesses of Margulis and Ramanujan-Margulis low-density parity-check cCodes. MFCSIT 2002: 97-104 - [i1]David J. Ward, David J. C. MacKay:
Fast Hands-free Writing by Gaze Direction. CoRR cs.HC/0204030 (2002) - 2001
- [j19]Virginia R. de Sa, David J. C. MacKay:
Model fitting as an aid to bridge balancing in neuronal recording. Neurocomputing 38-40: 1651-1656 (2001) - [j18]Matthew C. Davey, David J. C. MacKay:
Reliable communication over channels with insertions, deletions, and substitutions. IEEE Trans. Inf. Theory 47(2): 687-698 (2001) - [j17]David J. C. MacKay:
Errata for "Good error-correcting codes based on very sparse matrices". IEEE Trans. Inf. Theory 47(5): 2101 (2001) - [c12]David J. C. MacKay:
Almost-Certainly Runlength-Limiting Codes. IMACC 2001: 138-147 - 2000
- [j16]Mark N. Gibbs, David J. C. MacKay:
Variational Gaussian process classifiers. IEEE Trans. Neural Networks Learn. Syst. 11(6): 1458-1464 (2000) - [c11]David J. Ward, Alan F. Blackwell, David J. C. MacKay:
Dasher - a data entry interface using continuous gestures and language models. UIST 2000: 129-137
1990 – 1999
- 1999
- [j15]David J. C. MacKay:
Comparison of Approximate Methods for Handling Hyperparameters. Neural Comput. 11(5): 1035-1068 (1999) - [j14]David J. C. MacKay, Simon T. Wilson, Matthew C. Davey:
Comparison of constructions of irregular Gallager codes. IEEE Trans. Commun. 47(10): 1449-1454 (1999) - [j13]David J. C. MacKay:
Good Error-Correcting Codes Based on Very Sparse Matrices. IEEE Trans. Inf. Theory 45(2): 399-431 (1999) - [c10]Oliver B. Downs, David J. C. MacKay, Daniel D. Lee:
The Nonnegative Boltzmann Machine. NIPS 1999: 428-434 - 1998
- [j12]Matthew C. Davey, David J. C. MacKay:
Low-density parity check codes over GF(q). IEEE Commun. Lett. 2(6): 165-167 (1998) - [j11]Robert J. McEliece, David J. C. MacKay, Jung-Fu Cheng:
Turbo Decoding as an Instance of Pearl's "Belief Propagation" Algorithm. IEEE J. Sel. Areas Commun. 16(2): 140-152 (1998) - [j10]David J. C. MacKay:
Choice of Basis for Laplace Approximation. Mach. Learn. 33(1): 77-86 (1998) - [j9]David J. C. MacKay, Ryo Takeuchi:
Interpolation models with multiple hyperparameters. Stat. Comput. 8(1): 15-23 (1998) - [p1]David John Cameron MacKay:
Introduction to Monte Carlo Methods. Learning in Graphical Models 1998: 175-204 - 1997
- [c9]Brendan J. Frey, David J. C. MacKay:
A Revolution: Belief Propagation in Graphs with Cycles. NIPS 1997: 479-485 - 1996
- [j8]David J. C. MacKay:
Equivalence of Linear Boltzmann Chains and Hidden Markov Models. Neural Comput. 8(1): 178-181 (1996) - 1995
- [j7]David J. C. MacKay, Linda C. Bauman Peto:
A hierarchical Dirichlet language model. Nat. Lang. Eng. 1(3): 289-308 (1995) - [c8]David J. C. MacKay:
Good Codes Based on Very Sparse Matrices. IMACC 1995: 100-111 - [c7]Steve R. Waterhouse, David J. C. MacKay, Anthony J. Robinson:
Bayesian Methods for Mixtures of Experts. NIPS 1995: 351-357 - [c6]David J. C. MacKay:
Developments in Probabilistic Modelling with Neural Networks - Ensemble Learning. SNN Symposium on Neural Networks 1995: 191-198 - 1994
- [j6]Kenneth D. Miller, David J. C. MacKay:
The Role of Constraints in Hebbian Learning. Neural Comput. 6(1): 100-126 (1994) - [c5]David J. C. MacKay:
A Free Energy Minimization Framework for Inference Problems in modulo 2 Arithmetic. FSE 1994: 179-195 - 1993
- [c4]Steve Renals, David J. C. MacKay:
Bayesian regularisation methods in a hybrid MLP-HMM system. EUROSPEECH 1993: 1719-1722 - 1992
- [j5]David J. C. MacKay:
Bayesian Interpolation. Neural Comput. 4(3): 415-447 (1992) - [j4]David J. C. MacKay:
A Practical Bayesian Framework for Backpropagation Networks. Neural Comput. 4(3): 448-472 (1992) - [j3]David J. C. MacKay:
Information-Based Objective Functions for Active Data Selection. Neural Comput. 4(4): 590-604 (1992) - [j2]David J. C. MacKay:
The Evidence Framework Applied to Classification Networks. Neural Comput. 4(5): 720-736 (1992) - 1991
- [c3]David J. C. MacKay:
Bayesian Model Comparison and Backprop Nets. NIPS 1991: 839-846 - [c2]John S. Bridle, Anthony J. R. Heading, David J. C. MacKay:
Unsupervised Classifiers, Mutual Information and 'Phantom Targets'. NIPS 1991: 1096-1101 - 1990
- [j1]David J. C. MacKay, Kenneth D. Miller:
Analysis of Linsker's Simulations of Hebbian Rules. Neural Comput. 2(2): 173-187 (1990)
1980 – 1989
- 1989
- [c1]David J. C. MacKay, Kenneth D. Miller:
Analysis of Linsker's Simulations of Hebbian Rules. NIPS 1989: 694-701
Coauthor Index
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