Bayesian & Probabilistic

Efficient inference in matrix-variate Gaussian models with \iid observation noise NeurIPS 2011 EigenNet: A Bayesian hybrid of generative and conditional models for sparse learning NeurIPS 2011 Estimating time-varying input signals and ion channel states from a single voltage trace of a neuron NeurIPS 2011 Evaluating the inverse decision-making approach to preference learning NeurIPS 2011 Facial Expression Transfer with Input-Output Temporal Restricted Boltzmann Machines NeurIPS 2011 Fast Convergent Algorithms for Expectation Propagation Approximate Bayesian Inference AISTATS 2011 Faster Algorithms for Max-Product Message-Passing JMLR 2011 From Stochastic Nonlinear Integrate-and-Fire to Generalized Linear Models NeurIPS 2011 Gaussian process modulated renewal processes NeurIPS 2011 Gaussian Process Training with Input Noise NeurIPS 2011 Generalized Beta Mixtures of Gaussians NeurIPS 2011 Global Motion Planning under Uncertain Motion, Sensing, and Environment Map RSS 2011 Global Solution of Fully-Observed Variational Bayesian Matrix Factorization is Column-Wise Independent NeurIPS 2011 Heavy-tailed Distances for Gradient Based Image Descriptors NeurIPS 2011 Hidden-Unit Conditional Random Fields AISTATS 2011 Hierarchically Supervised Latent Dirichlet Allocation NeurIPS 2011 Hierarchical Topic Modeling for Analysis of Time-Evolving Personal Choices NeurIPS 2011 Inductive reasoning about chimeric creatures NeurIPS 2011 Inference in continuous-time change-point models NeurIPS 2011 Inferring Interaction Networks using the IBP applied to microRNA Target Prediction NeurIPS 2011 Inferring spike-timing-dependent plasticity from spike train data NeurIPS 2011 Infinite Latent SVM for Classification and Multi-task Learning NeurIPS 2011 Information Rates and Optimal Decoding in Large Neural Populations NeurIPS 2011 Kernel Bayes' Rule NeurIPS 2011 Kernel Belief Propagation AISTATS 2011