Probabilistic Modeling

Deterministic Anytime Inference for Stochastic Continuous-Time Markov Processes ICML 2014 Dirichlet-based Histogram Feature Transform for Image Classification CVPR 2014 Distributed Parameter Estimation in Probabilistic Graphical Models NeurIPS 2014 Diverse Sequential Subset Selection for Supervised Video Summarization NeurIPS 2014 Effective Bayesian Modeling of Groups of Related Count Time Series ICML 2014 Efficient Gradient-Based Inference through Transformations between Bayes Nets and Neural Nets ICML 2014 Efficient Inference for Complex Queries on Complex Distributions AISTATS 2014 Efficient Nonlinear Markov Models for Human Motion CVPR 2014 Efficient State-Space Inference of Periodic Latent Force Models JMLR 2014 Exchangeable Variable Models ICML 2014 Extended and Unscented Gaussian Processes NeurIPS 2014 Fast Allocation of Gaussian Process Experts ICML 2014 Fast Sampling-Based Inference in Balanced Neuronal Networks NeurIPS 2014 From MAP to Marginals: Variational Inference in Bayesian Submodular Models NeurIPS 2014 Fully Simplified Multivariate Normal Updates in Non-Conjugate Variational Message Passing JMLR 2014 Gaussian Process Classification and Active Learning with Multiple Annotators ICML 2014 Gaussian Processes for Bayesian Estimation in Ordinary Differential Equations ICML 2014 Generating Efficient MCMC Kernels from Probabilistic Programs AISTATS 2014 Global Sensitivity Analysis for MAP Inference in Graphical Models NeurIPS 2014 Graph-based Semi-supervised Learning: Realizing Pointwise Smoothness Probabilistically ICML 2014 Graphical Models for Recovering Probabilistic and Causal Queries from Missing Data NeurIPS 2014 Ground Plane Estimation using a Hidden Markov Model CVPR 2014 Hamming Ball Auxiliary Sampling for Factorial Hidden Markov Models NeurIPS 2014 Hardness of parameter estimation in graphical models NeurIPS 2014 Hierarchical Dirichlet Scaling Process ICML 2014