Probabilistic Modeling

Analytic Long-Term Forecasting with Periodic Gaussian Processes AISTATS 2014 A New Approach to Probabilistic Programming Inference AISTATS 2014 An Integer Polynomial Programming Based Framework for Lifted MAP Inference NeurIPS 2014 A Probabilistic Framework for Multimodal Retrieval using Integrative Indian Buffet Process NeurIPS 2014 A reversible infinite HMM using normalised random measures ICML 2014 Asynchronous Anytime Sequential Monte Carlo NeurIPS 2014 Augur: Data-Parallel Probabilistic Modeling NeurIPS 2014 Avoiding pathologies in very deep networks AISTATS 2014 Bat Call Identification with Gaussian Process Multinomial Probit Regression and a Dynamic Time Warping Kernel AISTATS 2014 Batch Continuous-Time Trajectory Estimation as Exactly Sparse Gaussian Process Regression RSS 2014 Bayesian Active Contours with Affine-Invariant, Elastic Shape Prior CVPR 2014 Bayesian Inference for Structured Spike and Slab Priors NeurIPS 2014 Bayesian Logistic Gaussian Process Models for Dynamic Networks AISTATS 2014 Bayesian Nonparametric Comorbidity Analysis of Psychiatric Disorders JMLR 2014 Bayesian View Synthesis and Image-Based Rendering Principles CVPR 2014 Belief propagation, robust reconstruction and optimal recovery of block models COLT 2014 Beta Diffusion Trees ICML 2014 Black Box Variational Inference AISTATS 2014 Blossom Tree Graphical Models NeurIPS 2014 Clamping Variables and Approximate Inference NeurIPS 2014 Clustered factor analysis of multineuronal spike data NeurIPS 2014 Color Transfer Using Probabilistic Moving Least Squares CVPR 2014 Concavity of reweighted Kikuchi approximation NeurIPS 2014 Conditional Random Field Autoencoders for Unsupervised Structured Prediction NeurIPS 2014 Decoupled Variational Gaussian Inference NeurIPS 2014