Probabilistic Modeling

Estimating time-varying input signals and ion channel states from a single voltage trace of a neuron NeurIPS 2011 Expressive Power and Approximation Errors of Restricted Boltzmann Machines NeurIPS 2011 Facial Expression Transfer with Input-Output Temporal Restricted Boltzmann Machines NeurIPS 2011 Generalised Coupled Tensor Factorisation 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 How biased are maximum entropy models? NeurIPS 2011 In All Likelihood, Deep Belief Is Not Enough JMLR 2011 Inductive reasoning about chimeric creatures NeurIPS 2011 Inferring spike-timing-dependent plasticity from spike train data NeurIPS 2011 Information Rates and Optimal Decoding in Large Neural Populations NeurIPS 2011 Inverting Grice's Maxims to Learn Rules from Natural Language Extractions NeurIPS 2011 Kernel Bayes' Rule NeurIPS 2011 Kernel Belief Propagation AISTATS 2011 Kernel Embeddings of Latent Tree Graphical Models NeurIPS 2011 Learning Higher-Order Graph Structure with Features by Structure Penalty NeurIPS 2011 Learning mixtures of Gaussians with maximum-a-posteriori oracle AISTATS 2011 Learning Probabilistic Non-Linear Latent Variable Models for Tracking Complex Activities NeurIPS 2011 Learning unbelievable probabilities NeurIPS 2011 Message-Passing for Approximate MAP Inference with Latent Variables NeurIPS 2011 Mixed Cumulative Distribution Networks AISTATS 2011