bayesian inference

Distributed Algorithms for Topic Models JMLR 2009 Explaining human multiple object tracking as resource-constrained approximate inference in a dynamic probabilistic model NeurIPS 2009 Hierarchical Learning of Dimensional Biases in Human Categorization NeurIPS 2009 Improving Existing Fault Recovery Policies 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 Marginal Likelihood Integrals for Mixtures of Independence Models JMLR 2009 Measuring model complexity with the prior predictive NeurIPS 2009 Modeling the spacing effect in sequential category learning NeurIPS 2009 Multi-Label Prediction via Sparse Infinite CCA NeurIPS 2009 Neural Implementation of Hierarchical Bayesian Inference by Importance Sampling NeurIPS 2009 Nonparametric Latent Feature Models for Link Prediction NeurIPS 2009 Perceptual Multistability as Markov Chain Monte Carlo Inference NeurIPS 2009 Perturbation Corrections in Approximate Inference: Mixture Modelling Applications JMLR 2009 Rethinking LDA: Why Priors Matter NeurIPS 2009 Sequential effects reflect parallel learning of multiple environmental regularities NeurIPS 2009 Speeding up Magnetic Resonance Image Acquisition by Bayesian Multi-Slice Adaptive Compressed Sensing NeurIPS 2009 The Hidden Life of Latent Variables: Bayesian Learning with Mixed Graph Models JMLR 2009 The Wisdom of Crowds in the Recollection of Order Information NeurIPS 2009 Variational Gaussian-process factor analysis for modeling spatio-temporal data NeurIPS 2009 Accelerating Bayesian Inference over Nonlinear Differential Equations with Gaussian Processes NeurIPS 2008