Probabilistic machine learning and artificial intelligence

On statistics, computation and scalability

(2013) Michael I. Jordan   BERNOULLI

Model-based machine learning

(2013) C. M. Bishop   PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES

Bayesian non-parametrics and the probabilistic approach to modelling

(2013) Z. Ghahramani   PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES

Deep Neural Networks for Acoustic Modeling in Speech Recognition: The Shared Views of Four Research Groups

(2012) Geoffrey Hinton et al.   IEEE SIGNAL PROCESSING MAGAZINE

The sequence memoizer

(2011) Frank Wood et al.   COMMUNICATIONS OF THE ACM

Riemann manifold Langevin and Hamiltonian Monte Carlo methods

(2011) Mark Girolami et al.   JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY

How to Grow a Mind: Statistics, Structure, and Abstraction

(2011) J. B. Tenenbaum et al.   SCIENCE

Modeling and Visualizing Uncertainty in Gene Expression Clusters Using Dirichlet Process Mixtures

(2009) C.E. Rasmussen et al.   IEEE-ACM Transactions on Computational Biology and Bioinformatics

Distilling Free-Form Natural Laws from Experimental Data

(2009) Michael Schmidt et al.   SCIENCE

Bayesian Spiking Neurons I: Inference

(2007) Sophie Deneve   NEURAL COMPUTATION