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Bayesian Learning

1663 directly classified papers

Papers per year

Papers

Large Scale Nonparametric Bayesian Inference: Data Parallelisation in the Indian Buffet Process NIPS 2009
Generalization Errors and Learning Curves for Regression with Multi-task Gaussian Processes NIPS 2009
Python Environment for Bayesian Learning: Inferring the Structure of Bayesian Networks from Knowledge and Data JMLR 2009
Robustness of the Unscented Kalman filter for state and parameter estimation in an elastic transmission RSS 2009
Identification of Recurrent Neural Networks by Bayesian Interrogation Techniques JMLR 2009
The Hidden Life of Latent Variables: Bayesian Learning with Mixed Graph Models JMLR 2009
Strong Limit Theorems for the Bayesian Scoring Criterion in Bayesian Networks JMLR 2009
Learning GP-BayesFilters via Gaussian process latent variable models RSS 2009
Bayesian Network Structure Learning by Recursive Autonomy Identification JMLR 2009
Marginal Likelihood Integrals for Mixtures of Independence Models JMLR 2009
A Bayesian Model for Simultaneous Image Clustering, Annotation and Object Segmentation NIPS 2009
Nonparametric Bayesian Texture Learning and Synthesis NIPS 2009
Indian Buffet Processes with Power-law Behavior NIPS 2009
A Bayesian Analysis of Dynamics in Free Recall NIPS 2009
Bayesian estimation of orientation preference maps NIPS 2009
The Infinite Partially Observable Markov Decision Process NIPS 2009
Bayesian Source Localization with the Multivariate Laplace Prior NIPS 2009
Non-Parametric Bayesian Dictionary Learning for Sparse Image Representations NIPS 2009
Variational Inference for the Nested Chinese Restaurant Process NIPS 2009
Posterior vs Parameter Sparsity in Latent Variable Models NIPS 2009
Time-Varying Dynamic Bayesian Networks NIPS 2009
Accelerating Bayesian Structural Inference for Non-Decomposable Gaussian Graphical Models NIPS 2009
Bayesian Sparse Factor Models and DAGs Inference and Comparison NIPS 2009
Construction of Nonparametric Bayesian Models from Parametric Bayes Equations NIPS 2009
Neural Implementation of Hierarchical Bayesian Inference by Importance Sampling NIPS 2009