Probabilistic Modeling

Lifted Hybrid Variational Inference IJCAI 2020 Lifted Query Answering in Gaussian Bayesian Networks PGM 2020 LMLFM: Longitudinal Multi-Level Factorization Machine AAAI 2020 Logsmooth Gradient Concentration and Tighter Runtimes for Metropolized Hamiltonian Monte Carlo COLT 2020 Low-dimensional statistical manifold embedding of directed graphs ICLR 2020 Lower Bounds for Testing Graphical Models: Colorings and Antiferromagnetic Ising Models JMLR 2020 Matérn Gaussian Processes on Riemannian Manifolds NeurIPS 2020 McFlow: Monte Carlo Flow Models for Data Imputation CVPR 2020 Missing Values in Multiple Joint Inference of Gaussian Graphical Models PGM 2020 Mixture Dense Regression for Object Detection and Human Pose Estimation CVPR 2020 Neural Belief Reasoner IJCAI 2020 Neural Dialogue State Tracking with Temporally Expressive Networks EMNLP 2020 New Off-Board Solution for Predicting Vehicles' Intentions in the Highway On-Ramp Using Probabilistic Classifiers (Student Abstract) AAAI 2020 Noise-Contrastive Estimation for Multivariate Point Processes NeurIPS 2020 Nonconvex Sparse Graph Learning under Laplacian Constrained Graphical Model NeurIPS 2020 Non-exchangeable feature allocation models with sublinear growth of the feature sizes AISTATS 2020 Non-Parametric Calibration for Classification AISTATS 2020 Nonparametric graphical model for counts JMLR 2020 On Application of Bayesian Parametric and Non-parametric Methods for User Cohorting in Product Search ACL 2020 On Relativistic f-Divergences ICML 2020 On Simulation and Trajectory Prediction with Gaussian Process Dynamics L4DC 2020 On the Relationship Between Probabilistic Circuits and Determinantal Point Processes UAI 2020 On the Theoretical Guarantees for Parameter Estimation of Gaussian Random Field Models: A Sparse Precision Matrix Approach JMLR 2020 Ordering Variables for Weighted Model Integration UAI 2020 Parallel AND/OR Search for Marginal MAP AAAI 2020