Rao−Blackwellised particle filtering for fault diagnosis by de Freitas, N

Intracluster Moves for Constrained Discrete−Space MCMC by Hamze, F, de Freitas, N

Asymptotic Efficiency of Deterministic Estimators for Discrete Energy−Based Models: Ratio Matching and Pseudolikelihood by Marlin, B, de Freitas, N

A Machine Learning Perspective on Predictive Coding with PAQ8 by Knoll, B, de Freitas, N

From Fields to Trees by Hamze, F, de Freitas, N

Learning about individuals from group statistics by Kuck, H, de Freitas, N

Why can't read?: the problem of learning semantic associations in a robot environment by Carbonetto, P, de Freitas, N

Theoretical Analysis of Bayesian Optimisation with Unknown Gaussian Process Hyper−Parameters by Wang, Z, de Freitas, N

Beat Tracking the Graphical Model Way by Lang, D, de Freitas, N

Sequential Monte Carlo for model selection and estimation of neural networks by Andrieu, C, de Freitas, N

Inference Strategies for Solving Semi−Markov Decision Processes by Hoffman, M, de Freitas, N

Hot Coupling: A Particle Approach to Inference and Normalization on Pairwise Undirected Graphs by Hamze, F, De Freitas, N

Target−directed attention: Sequential decision−making for gaze planning by Vogel, J, de Freitas, N

A Blessing of Dimensionality: Measure Concentration and Probabilistic Inference by Muyan, P, de Freitas, N

Toward the Implementation of a Quantum RBM by Denil, M, de Freitas, N

Adaptive Hamiltonian and Riemann Manifold Monte Carlo Samplers by Wang, Z, Mohamed, S, de Freitas, N

A Bayesian interactive optimization approach to procedural animation design by Brochu, E, Brochu, T, de Freitas, N

Distributed Parameter Estimation in Probabilistic Graphical Models by Mizrahi, Y, Denil, M, de Freitas, N

Sequential MCMC for Bayesian model selection by Andrieu, C, De Freitas, N, Doucet, A

Robust Full Bayesian Learning for Radial Basis Networks by Andrieu, C, De Freitas, N, Doucet, A