Bayesian Inference

Decoupling Sparsity and Smoothness in the Discrete Hierarchical Dirichlet Process NeurIPS 2009 Distributed Algorithms for Topic Models JMLR 2009 Explaining human multiple object tracking as resource-constrained approximate inference in a dynamic probabilistic model NeurIPS 2009 Free energy score space NeurIPS 2009 From PAC-Bayes Bounds to KL Regularization NeurIPS 2009 Gaussian process regression with Student-t likelihood NeurIPS 2009 Graph Zeta Function in the Bethe Free Energy and Loopy Belief Propagation NeurIPS 2009 Help or Hinder: Bayesian Models of Social Goal Inference NeurIPS 2009 Hierarchical Learning of Dimensional Biases in Human Categorization NeurIPS 2009 Inter-domain Gaussian Processes for Sparse Inference using Inducing Features NeurIPS 2009 Know Thy Neighbour: A Normative Theory of Synaptic Depression NeurIPS 2009 Large Scale Nonparametric Bayesian Inference: Data Parallelisation in the Indian Buffet Process NeurIPS 2009 Learning models of object structure NeurIPS 2009 Learning with Compressible Priors NeurIPS 2009 Linearly constrained Bayesian matrix factorization for blind source separation NeurIPS 2009 Localizing Bugs in Program Executions with Graphical Models NeurIPS 2009 Manifold Regularization for SIR with Rate Root-n Convergence NeurIPS 2009 Measuring model complexity with the prior predictive NeurIPS 2009 Modeling the spacing effect in sequential category learning NeurIPS 2009 Modelling Relational Data using Bayesian Clustered Tensor Factorization NeurIPS 2009 Multi-Label Prediction via Sparse Infinite CCA NeurIPS 2009 Neural Implementation of Hierarchical Bayesian Inference by Importance Sampling NeurIPS 2009 Nonlinear Models Using Dirichlet Process Mixtures JMLR 2009 Nonparametric Bayesian Models for Unsupervised Event Coreference Resolution NeurIPS 2009 Nonparametric Bayesian Texture Learning and Synthesis NeurIPS 2009