图书简介

1 Introduction to Bayesian inference; 2 Asymptotic inference and information; 3 High-dimensional inference: searching for principal components; 4 Priors, regularisation, sparsity; 5 Graphical models: from network reconstruction to Boltzmann machines; 6 Unsupervised learning: from representations to generative models; 7 Supervised learning: classification with neural networks; 8 Time series: from Markov models to hidden Markov models

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