Bayesian Learning

Modelling Genetic Variations using Fragmentation-Coagulation Processes NeurIPS 2011 Multiscale Community Blockmodel for Network Exploration AISTATS 2011 Non-conjugate Variational Message Passing for Multinomial and Binary Regression NeurIPS 2011 Nonlinear Inverse Reinforcement Learning with Gaussian Processes NeurIPS 2011 On the Analysis of Multi-Channel Neural Spike Data NeurIPS 2011 Optimal Reinforcement Learning for Gaussian Systems NeurIPS 2011 Parallel Algorithm for Learning Optimal Bayesian Network Structure JMLR 2011 Practical Variational Inference for Neural Networks NeurIPS 2011 Priors over Recurrent Continuous Time Processes NeurIPS 2011 Quasi-Newton Methods for Markov Chain Monte Carlo NeurIPS 2011 Robust Multi-Class Gaussian Process Classification NeurIPS 2011 Sparse Bayesian Multi-Task Learning NeurIPS 2011 Spatial distance dependent Chinese restaurant processes for image segmentation NeurIPS 2011 Spectral Chinese Restaurant Processes: Nonparametric Clustering Based on Similarities AISTATS 2011 Spike and Slab Variational Inference for Multi-Task and Multiple Kernel Learning NeurIPS 2011 Switch-Reset Models : Exact and Approximate Inference AISTATS 2011 Testing a Bayesian Measure of Representativeness Using a Large Image Database NeurIPS 2011 The Discrete Infinite Logistic Normal Distribution for Mixed-Membership Modeling AISTATS 2011 The Doubly Correlated Nonparametric Topic Model NeurIPS 2011 The Kernel Beta Process NeurIPS 2011 The Sample Complexity of Self-Verifying Bayesian Active Learning AISTATS 2011 Variational Gaussian Process Dynamical Systems NeurIPS 2011 A Bayesian Approach to Concept Drift NeurIPS 2010 A Bayesian Framework for Figure-Ground Interpretation NeurIPS 2010 A rational decision making framework for inhibitory control NeurIPS 2010