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Bayesian Learning

1663 directly classified papers

Papers per year

Papers

Modelling transcriptional regulation using Gaussian Processes NIPS 2006
Mixture Regression for Covariate Shift NIPS 2006
Context Effects in Category Learning: An Investigation of Four Probabilistic Models NIPS 2006
Causal inference in sensorimotor integration NIPS 2006
PAC-Bayes Bounds for the Risk of the Majority Vote and the Variance of the Gibbs Classifier NIPS 2006
Data Integration for Classification Problems Employing Gaussian Process Priors NIPS 2006
Optimal Change-Detection and Spiking Neurons NIPS 2006
Bayesian Image Super-resolution, Continued NIPS 2006
Combining causal and similarity-based reasoning NIPS 2006
Learning to be Bayesian without Supervision NIPS 2006
Bayesian Network Learning with Parameter Constraints JMLR 2006
Hierarchical Dirichlet Processes with Random Effects NIPS 2006
Bayesian Model Scoring in Markov Random Fields NIPS 2006
Particle Filtering for Nonparametric Bayesian Matrix Factorization NIPS 2006
A Bayesian Approach to Diffusion Models of Decision-Making and Response Time NIPS 2006
A Collapsed Variational Bayesian Inference Algorithm for Latent Dirichlet Allocation NIPS 2006
A Scoring Function for Learning Bayesian Networks based on Mutual Information and Conditional Independence Tests JMLR 2006
Dynamic Imitation in a Humanoid Robot through Nonparametric Probabilistic Inference RSS 2006
Dirichlet-Enhanced Spam Filtering based on Biased Samples NIPS 2006
Analysis of Empirical Bayesian Methods for Neuroelectromagnetic Source Localization NIPS 2006
A Nonparametric Bayesian Method for Inferring Features From Similarity Judgments NIPS 2006
Accelerated Variational Dirichlet Process Mixtures NIPS 2006
Bayesian Detection of Infrequent Differences in Sets of Time Series with Shared Structure NIPS 2006
Hidden Markov Dirichlet Process: Modeling Genetic Recombination in Open Ancestral Space NIPS 2006
Bayesian Ensemble Learning NIPS 2006