Cavendish Astrophysics Publications for author : DJC Mackay

  1. MacKay, D.J.C., 1992. Bayesian Interpolation. Neural Computation, 4, 3.

  2. MacKay, D.J.C., 1992. A practical Bayesian framework for backpropagation networks. Neural Computation, 4, 3.

  3. MacKay, D.J.C., 1992. Information based objective functions for active data selection. Neural Computation, 4, 589-603.

  4. MacKay, D.J.C., 1992. The evidence framework applied to classification networks. Neural Computation, 4, 698-714.

  5. MacKay, D.J.C., 1995. A free energy minimization algorithm for decoding and cryptanalysis. Electronics Letters, 31, 446-447.

  6. Renals, S.J., MacKay, D.J.C., 1993. Bayesian regularisation methods in a hybrid MLP-HMM system. Proceedings, Eurospeech, 1719-1722.

  7. Miller, K.D., MacKay, D.J.C., 1994. The role of constraints in Hebbian learning. Neural Computation, 6, 98-124.

  8. Bhadeshia, H.K.D.H., MacKay, D.J.C., Svensson, L.E., 1995. Impact toughness of C-Mn steel arc welds - Bayesian neural network analysis. Materials Science & Technology, 11, 1046-1051.

  9. Takeuchi, R., MacKay, D.J.C., Matsumoto, T., 1994. Determining optimal hyperparameters and regularizers for standard regularization problems. International Symposium on Artificial Neural Networks (ISANN-94)., 419-428.

  10. MacKay, D.J.C., Peto, L., 1995. A hierarchical Dirichlet language model. Natural Language Engineering, 1, 1-19.

  11. MacKay, D.J.C., 1995. Probable networks and plausible predictions - a review of practical Bayesian methods for supervised neural networks. Network: Computation in Neural Systems, 6, 469-505.

  12. MacKay, D.J.C., 1994. Bayesian non-linear modelling for the prediction competition. ASHRAE Transactions, ASHRAE, 100(2), 1053-1056.

  13. Tansley, J.E., Oldfield, M.J., MacKay, D.J.C., 1996. Neural network image reconstruction. Maximum Entropy & Bayesian Methods, G. Heidbreder, Kluwer, Dordrecht, 319-326.

  14. MacKay, D.J.C., Takeuchi, R., 1995. Interpolation models with multiple hyperparameters. Maximum Entropy & Bayesian Methods, J. Skilling, S. Sibisi, Kluwer, 249-257. Link

  15. Barnett, A.H., MacKay, D.J.C., 1995. Bayesian comparison of models for images. Maximum Entropy & Bayesian Methods, J. Skilling, S. Sibisi, Kluwer, 239-248. Link

  16. MacKay, D.J.C., 1995. Density networks and their application to protein modelling. Maximum Entropy & Bayesian Methods, J. Skilling, S. Sibisi, Kluwer, 259-268. Link

  17. MacKay, D.J.C., 1995. Bayesian neural networks and density networks. Nuclear Instruments & Methods in Phys. Res. A, 354, 73-80. Link

  18. Takeuchi, R., MacKay, D.J.C., Matsumoto, T., 1994. A Bayesian inference of hyperparameters and regularizers for standard regularization problems (Japanese). Technical report of IEICE, in press.

  19. Gavard, L., Bhadeshia, H.K.D.H., MacKay, D.C., Suzuki, S., 1996. Bayesian Neural Network Model for Austenite Formation in Steels. Materials Science & Technology, 12, 453-463.

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