Probabilistic Modeling

Learning Chordal Markov Networks via Branch and Bound NeurIPS 2017 Learning Determinantal Point Processes with Moments and Cycles ICML 2017 Learning from Clinical Judgments: Semi-Markov-Modulated Marked Hawkes Processes for Risk Prognosis ICML 2017 Learning Identifiable Gaussian Bayesian Networks in Polynomial Time and Sample Complexity NeurIPS 2017 Learning Local Dependence In Ordered Data JMLR 2017 Learning the Morphology of Brain Signals Using Alpha-Stable Convolutional Sparse Coding NeurIPS 2017 Learning the Structure of Variable-Order CRFs: a finite-state perspective EMNLP 2017 Learning to Detect Sepsis with a Multitask Gaussian Process RNN Classifier ICML 2017 Linearly constrained Gaussian processes NeurIPS 2017 Linear Time Computation of Moments in Sum-Product Networks NeurIPS 2017 Locally Consistent Bayesian Network Scores for Multi-Relational Data IJCAI 2017 Local Perturb-and-MAP for Structured Prediction AISTATS 2017 LoCaTe: Influence Quantification for Location Promotion in Location-based Social Networks IJCAI 2017 Logic meets Probability: Towards Explainable AI Systems for Uncertain Worlds IJCAI 2017 Logistic Markov Decision Processes IJCAI 2017 Lost Relatives of the Gumbel Trick ICML 2017 Markov Chain Truncation for Doubly-Intractable Inference AISTATS 2017 Model-based Bayesian inference of neural activity and connectivity from all-optical interrogation of a neural circuit NeurIPS 2017 Most Probable Explanations for Probabilistic Database Queries IJCAI 2017 Neural Graphical Models over Strings for Principal Parts Morphological Paradigm Completion EACL 2017 Non-Count Symmetries in Boolean & Multi-Valued Prob. Graphical Models AISTATS 2017 Online but Accurate Inference for Latent Variable Models with Local Gibbs Sampling JMLR 2017 On Relaxing Determinism in Arithmetic Circuits ICML 2017 Optimal Feature Selection for Decision Robustness in Bayesian Networks IJCAI 2017 Order Statistics for Probabilistic Graphical Models IJCAI 2017