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Bayesian Learning

1663 directly classified papers

Papers per year

Papers

Nonlinear Inverse Reinforcement Learning with Gaussian Processes NIPS 2011
Spike and Slab Variational Inference for Multi-Task and Multiple Kernel Learning NIPS 2011
Variational Gaussian Process Dynamical Systems NIPS 2011
Generalized Beta Mixtures of Gaussians NIPS 2011
Gaussian Process Training with Input Noise NIPS 2011
Infinite Latent SVM for Classification and Multi-task Learning NIPS 2011
Hierarchical Topic Modeling for Analysis of Time-Evolving Personal Choices NIPS 2011
Learning to Learn with Compound HD Models NIPS 2011
Modelling Genetic Variations using Fragmentation-Coagulation Processes NIPS 2011
Kernel Bayes' Rule NIPS 2011
Sparse Bayesian Multi-Task Learning NIPS 2011
Additive Gaussian Processes NIPS 2011
Spatial distance dependent Chinese restaurant processes for image segmentation NIPS 2011
MAP Inference for Bayesian Inverse Reinforcement Learning NIPS 2011
Testing a Bayesian Measure of Representativeness Using a Large Image Database NIPS 2011
Automated Refinement of Bayes Networks' Parameters based on Test Ordering Constraints NIPS 2011
Analytical Results for the Error in Filtering of Gaussian Processes NIPS 2011
The Doubly Correlated Nonparametric Topic Model NIPS 2011
Active learning of neural response functions with Gaussian processes NIPS 2011
On the Analysis of Multi-Channel Neural Spike Data NIPS 2011
Bayesian Bias Mitigation for Crowdsourcing NIPS 2011
The Kernel Beta Process NIPS 2011
Priors over Recurrent Continuous Time Processes NIPS 2011
Convergence Rates of Efficient Global Optimization Algorithms JMLR 2011
Logistic Stick-Breaking Process JMLR 2011