MacKay, David J. C.

A practical Bayesian framework for backpropagation networks

MacKay, D. J. C. (1992) · Neural Computation

Neural Networks and ApplicationsGaussian Processes and Bayesian Inference

Cited by 2,917

Information-based objective functions for active data selection

MacKay, D. J. C. (1992) · Neural Computation

Machine Learning and AlgorithmsGaussian Processes and Bayesian Inference

Cited by 1,221

Probable networks and plausible predictions — a review of practical Bayesian methods for supervised neural networks

Mackay, D. J. C. (1995) · Network Computation in Neural Systems

Gaussian Processes and Bayesian InferenceNeural Networks and Applications

Cited by 915

Bayesian Online Changepoint Detection

Adams, R. P., & MacKay, D. J. C. (2007) · arXiv

Advanced Statistical Process MonitoringData Stream Mining Techniques

Cited by 601

The Role of Constraints in Hebbian Learning

Miller, K. D., & MacKay, D. J. C. (1994) · Neural Computation

Neural Networks and ApplicationsNeural dynamics and brain function

Cited by 448

Gaussian process robust regression for noisy heart rate data

Stegle, O., Fallert, S. V., MacKay, D. J. C., & Brage, S. (2008) · IEEE Transactions on Biomedical Engineering

Non-Invasive Vital Sign MonitoringGaussian Processes and Bayesian Inference

Cited by 213

Free energy minimisation algorithmfor decoding and cryptanalysis

MacKay, D. J. C. (1995) · Electronics Letters

Coding theory and cryptographyError Correcting Code Techniques

Cited by 79