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Probabilistic Modeling

1884 directly classified papers

Papers per year

Papers

Scalable MAP inference in Bayesian networks based on a Map-Reduce approach PGM 2016
Evidence Evaluation: a Study of Likelihoods and Independence PGM 2016
Bayesian Networks for Variable Groups PGM 2016
Dynamic Sum Product Networks for Tractable Inference on Sequence Data PGM 2016
The Effect of Combination Functions on the Complexity of Relational Bayesian Networks PGM 2016
Joint Bayesian Modelling of Internal Dependencies and Relevant Multimorbidities of a Heterogeneous Disease PGM 2016
Estimating Causal Effects with Ancestral Graph Markov Models PGM 2016
Multi-Label Classification with Cutset Networks PGM 2016
Probabilistic Approaches to the AXB = YCZ Calibration Problem in Multi-Robot Systems RSS 2016
D-GloVe: A Feasible Least Squares Model for Estimating Word Embedding Densities COLING 2016
Modeling topic dependencies in semantically coherent text spans with copulas COLING 2016
Hierarchical Probabilistic Matrix Factorization with Network Topology for Multi-relational Social Network ACML 2016
Unifying Topic, Sentiment & Preference in an HDP-Based Rating Regression Model for Online Reviews ACML 2016
Compressing Bayes Net CPTs with Persistent Leaky Causes PGM 2016
Computing Lower and Upper Bounds on the Probability of Causal Statements PGM 2016
Exact Inference on Conditional Linear Γ-Gaussian Bayesian Networks PGM 2016
Identifying the irreducible disjoint factors of a multivariate probability distribution PGM 2016
Learning Complex Uncertain States Changes via Asymmetric Hidden Markov Models: an Industrial Case PGM 2016
Bayesian Networks: a Combined Tuning Heuristic PGM 2016
Learning Tractable Multidimensional Bayesian Network Classifiers PGM 2016
Natural-Parameter Networks: A Class of Probabilistic Neural Networks NIPS 2016
Kronecker Determinantal Point Processes NIPS 2016
Learning HMMs with Nonparametric Emissions via Spectral Decompositions of Continuous Matrices NIPS 2016
Geometric Dirichlet Means Algorithm for topic inference NIPS 2016
Variational Inference in Mixed Probabilistic Submodular Models NIPS 2016