Bayesian Learning

Neural characterization in partially observed populations of spiking neurons NeurIPS 2007 On Sparsity and Overcompleteness in Image Models NeurIPS 2007 Privacy-Preserving Belief Propagation and Sampling NeurIPS 2007 Regulator Discovery from Gene Expression Time Series of Malaria Parasites: a Hierachical Approach NeurIPS 2007 Robust Regression with Twinned Gaussian Processes NeurIPS 2007 Sequential Hypothesis Testing under Stochastic Deadlines NeurIPS 2007 The Generalized FITC Approximation NeurIPS 2007 The Infinite Gamma-Poisson Feature Model NeurIPS 2007 The Infinite Markov Model NeurIPS 2007 The rat as particle filter NeurIPS 2007 Transfer Learning using Kolmogorov Complexity: Basic Theory and Empirical Evaluations NeurIPS 2007 TrueSkill Through Time: Revisiting the History of Chess NeurIPS 2007 Using Deep Belief Nets to Learn Covariance Kernels for Gaussian Processes NeurIPS 2007 Variational inference for Markov jump processes NeurIPS 2007 A Bayesian Approach to Diffusion Models of Decision-Making and Response Time NeurIPS 2006 Accelerated Variational Dirichlet Process Mixtures NeurIPS 2006 A Collapsed Variational Bayesian Inference Algorithm for Latent Dirichlet Allocation NeurIPS 2006 Adaptor Grammars: A Framework for Specifying Compositional Nonparametric Bayesian Models NeurIPS 2006 Analysis of Empirical Bayesian Methods for Neuroelectromagnetic Source Localization NeurIPS 2006 A Nonparametric Bayesian Method for Inferring Features From Similarity Judgments NeurIPS 2006 A Scoring Function for Learning Bayesian Networks based on Mutual Information and Conditional Independence Tests JMLR 2006 Bayesian Detection of Infrequent Differences in Sets of Time Series with Shared Structure NeurIPS 2006 Bayesian Ensemble Learning NeurIPS 2006 Bayesian Image Super-resolution, Continued NeurIPS 2006 Bayesian Model Scoring in Markov Random Fields NeurIPS 2006