probabilistic modeling

Deep Gaussian Conditional Random Field Network: A Model-Based Deep Network for Discriminative Denoising CVPR 2016 D-GloVe: A Feasible Least Squares Model for Estimating Word Embedding Densities COLING 2016 Edge-exchangeable graphs and sparsity NeurIPS 2016 Evidence Evaluation: a Study of Likelihoods and Independence PGM 2016 Exact Exponent in Optimal Rates for Crowdsourcing ICML 2016 Exact Inference on Conditional Linear Γ-Gaussian Bayesian Networks PGM 2016 Exploring Differential Topic Models for Comparative Summarization of Scientific Papers COLING 2016 Exponential Family Embeddings NeurIPS 2016 Generative Acoustic-Phonemic-Speaker Model Based on Three-Way Restricted Boltzmann Machine Interspeech 2016 Hybrid Copula Bayesian Networks PGM 2016 Identifying the irreducible disjoint factors of a multivariate probability distribution PGM 2016 Kronecker Determinantal Point Processes NeurIPS 2016 Learnability of Non-I.I.D. ACML 2016 Learning Probabilistic Submodular Diversity Models Via Noise Contrastive Estimation AISTATS 2016 Learning Tractable Multidimensional Bayesian Network Classifiers PGM 2016 Modeling topic dependencies in semantically coherent text spans with copulas COLING 2016 Natural-Parameter Networks: A Class of Probabilistic Neural Networks NeurIPS 2016 Nonlinear Statistical Learning with Truncated Gaussian Graphical Models ICML 2016 Optimality of Belief Propagation for Crowdsourced Classification ICML 2016 Pairwise Choice Markov Chains NeurIPS 2016 PHOG: Probabilistic Model for Code ICML 2016 Poisson-Gamma dynamical systems NeurIPS 2016 Probabilistic Approaches to the AXB = YCZ Calibration Problem in Multi-Robot Systems RSS 2016 Probabilistic Prototype Model for Serendipitous Property Mining COLING 2016 Reintroducing Credal Networks under Epistemic Irrelevance PGM 2016