Bayesian & Probabilistic

EigenNet: A Bayesian hybrid of generative and conditional models for sparse learning NeurIPS 2011 Empirical models of spiking in neural populations NeurIPS 2011 Estimating time-varying input signals and ion channel states from a single voltage trace of a neuron NeurIPS 2011 Evolving Cluster Mixed-Membership Blockmodel for Time-Evolving Networks AISTATS 2011 Expressive Power and Approximation Errors of Restricted Boltzmann Machines 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 Gaussian process modulated renewal processes NeurIPS 2011 Gaussian Process Training with Input Noise NeurIPS 2011 Generalised Coupled Tensor Factorisation NeurIPS 2011 Generalized Beta Mixtures of Gaussians NeurIPS 2011 Generative Kernels for Exponential Families AISTATS 2011 Group Anomaly Detection using Flexible Genre Models 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 Probabilistic Models for Group Anomaly Detection AISTATS 2011 Hierarchical Topic Modeling for Analysis of Time-Evolving Personal Choices NeurIPS 2011 How biased are maximum entropy models? NeurIPS 2011 Image Parsing with Stochastic Scene Grammar NeurIPS 2011 In All Likelihood, Deep Belief Is Not Enough JMLR 2011 Inductive reasoning about chimeric creatures 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