Bayesian & Probabilistic

Stochastic Regret Minimization via Thompson Sampling COLT 2014 Stochastic variational inference for hidden Markov models NeurIPS 2014 Structured Recurrent Temporal Restricted Boltzmann Machines ICML 2014 Structure learning of antiferromagnetic Ising models NeurIPS 2014 Student-t Processes as Alternatives to Gaussian Processes AISTATS 2014 The Bayesian Case Model: A Generative Approach for Case-Based Reasoning and Prototype Classification NeurIPS 2014 The Infinite Mixture of Infinite Gaussian Mixtures NeurIPS 2014 Thompson Sampling for Complex Online Problems ICML 2014 Tilted Variational Bayes AISTATS 2014 Tracking on the Product Manifold of Shape and Orientation for Tractography from Diffusion MRI CVPR 2014 Transportability from Multiple Environments with Limited Experiments: Completeness Results NeurIPS 2014 Tree-structured Gaussian Process Approximations NeurIPS 2014 Understanding Protein Dynamics with L1-Regularized Reversible Hidden Markov Models ICML 2014 Unsupervised Transcription of Piano Music NeurIPS 2014 Variational Gaussian Inference for Bilinear Models of Count Data ACML 2014 Variational Gaussian Process State-Space Models NeurIPS 2014 Variational Inference for Sequential Distance Dependent Chinese Restaurant Process ICML 2014 Active Bayesian Perception for Simultaneous Object Localization and Identification RSS 2013 Active Learning for Probabilistic Hypotheses Using the Maximum Gibbs Error Criterion NeurIPS 2013 Active Visual Recognition with Expertise Estimation in Crowdsourcing ICCV 2013 Adaptive Hamiltonian and Riemann Manifold Monte Carlo ICML 2013 A Deep Sum-Product Architecture for Robust Facial Attributes Analysis ICCV 2013 A Determinantal Point Process Latent Variable Model for Inhibition in Neural Spiking Data NeurIPS 2013 A Framework for Evaluating Approximation Methods for Gaussian Process Regression JMLR 2013 A Graphical Transformation for Belief Propagation: Maximum Weight Matchings and Odd-Sized Cycles NeurIPS 2013