MacKay, David J. C.

16 publications

ICML 2009 Tractable Nonparametric Bayesian Inference in Poisson Processes with Gaussian Process Intensities Ryan Prescott Adams, Iain Murray, David J. C. MacKay

UAI 2006 MCMC for Doubly-Intractable Distributions Iain Murray, Zoubin Ghahramani, David J. C. MacKay

NeCo 1999 Comparison of Approximate Methods for Handling Hyperparameters David J. C. MacKay

NeurIPS 1999 The Nonnegative Boltzmann Machine Oliver B. Downs, David J. C. MacKay, Daniel D. Lee

MLJ 1998 Choice of Basis for Laplace Approximation David J. C. MacKay

NeurIPS 1997 A Revolution: Belief Propagation in Graphs with Cycles Brendan J. Frey, David J. C. MacKay

NeCo 1996 Equivalence of Linear Boltzmann Chains and Hidden Markov Models David J. C. MacKay

NeCo 1994 The Role of Constraints in Hebbian Learning Kenneth D. Miller, David J. C. MacKay

NeCo 1992 A Practical Bayesian Framework for Backpropagation Networks David J. C. MacKay

NeCo 1992 Bayesian Interpolation David J. C. MacKay

NeCo 1992 Information-Based Objective Functions for Active Data Selection David J. C. MacKay

NeCo 1992 The Evidence Framework Applied to Classification Networks David J. C. MacKay

NeurIPS 1991 Bayesian Model Comparison and Backprop Nets David J. C. MacKay

NeurIPS 1991 Unsupervised Classifiers, Mutual Information and 'Phantom Targets John S. Bridle, Anthony J. R. Heading, David J. C. MacKay

NeCo 1990 Analysis of Linsker's Simulations of Hebbian Rules David J. C. MacKay, Kenneth D. Miller

NeurIPS 1989 Analysis of Linsker's Simulations of Hebbian Rules David J. C. MacKay, Kenneth D. Miller