Bayesian Learning

Bayesian Network Learning with Parameter Constraints JMLR 2006 Bayesian Policy Gradient Algorithms NeurIPS 2006 Causal inference in sensorimotor integration NeurIPS 2006 Combining causal and similarity-based reasoning NeurIPS 2006 Context Effects in Category Learning: An Investigation of Four Probabilistic Models NeurIPS 2006 Data Integration for Classification Problems Employing Gaussian Process Priors NeurIPS 2006 Dirichlet-Enhanced Spam Filtering based on Biased Samples NeurIPS 2006 Dynamic Imitation in a Humanoid Robot through Nonparametric Probabilistic Inference RSS 2006 Hidden Markov Dirichlet Process: Modeling Genetic Recombination in Open Ancestral Space NeurIPS 2006 Hierarchical Dirichlet Processes with Random Effects NeurIPS 2006 Learning Time-Intensity Profiles of Human Activity using Non-Parametric Bayesian Models NeurIPS 2006 Learning to be Bayesian without Supervision NeurIPS 2006 Mixture Regression for Covariate Shift NeurIPS 2006 Modeling Dyadic Data with Binary Latent Factors NeurIPS 2006 Modelling transcriptional regulation using Gaussian Processes NeurIPS 2006 Multiple timescales and uncertainty in motor adaptation NeurIPS 2006 Optimal Change-Detection and Spiking Neurons NeurIPS 2006 PAC-Bayes Bounds for the Risk of the Majority Vote and the Variance of the Gibbs Classifier NeurIPS 2006 Parameter Expanded Variational Bayesian Methods NeurIPS 2006 Particle Filtering for Nonparametric Bayesian Matrix Factorization NeurIPS 2006 TrueSkill™: A Bayesian Skill Rating System NeurIPS 2006 Unified Inference for Variational Bayesian Linear Gaussian State-Space Models NeurIPS 2006 Inner Product Spaces for Bayesian Networks JMLR 2005 Local Propagation in Conditional Gaussian Bayesian Networks JMLR 2005 Exact Bayesian Structure Discovery in Bayesian Networks JMLR 2004