Bayesian & Probabilistic

Convergence Rates of Gradient Descent and MM Algorithms for Bradley-Terry Models AISTATS 2020 Correcting Predictions for Approximate Bayesian Inference AAAI 2020 Correlated Equilibria for Approximate Variational Inference in MRFs PGM 2020 CREDICI: A Java Library for Causal Inference by Credal Networks PGM 2020 CREMA: A Java Library for Credal Network Inference PGM 2020 Cyclical Stochastic Gradient MCMC for Bayesian Deep Learning ICLR 2020 DAGs with No Fears: A Closer Look at Continuous Optimization for Learning Bayesian Networks NeurIPS 2020 Data-Dependent Differentially Private Parameter Learning for Directed Graphical Models ICML 2020 Data-dependent Gaussian Prior Objective for Language Generation ICLR 2020 Deep active inference agents using Monte-Carlo methods NeurIPS 2020 Deep Bayesian Network for Visual Question Generation WACV 2020 Deep Gaussian Markov Random Fields ICML 2020 Deep Generalized Convolutional Sum-Product Networks PGM 2020 Deep Mixed Effect Model Using Gaussian Processes: A Personalized and Reliable Prediction for Healthcare AAAI 2020 Deep Orientation Uncertainty Learning based on a Bingham Loss ICLR 2020 Deep Sigma Point Processes UAI 2020 Design Adaptive AI for RTS Game by Learning Player's Build Order IJCAI 2020 Differentiable Algorithm for Marginalising Changepoints AAAI 2020 Differentiable TAN Structure Learning for Bayesian Network Classifiers PGM 2020 Discriminative Non-Parametric Learning of Arithmetic Circuits PGM 2020 Disentangled Representations for Sequence Data using Information Bottleneck Principle ACML 2020 Distortion estimates for approximate Bayesian inference UAI 2020 Distributionally Ambiguous Optimization for Batch Bayesian Optimization JMLR 2020 Distributionally Robust Bayesian Optimization AISTATS 2020 Divergence-Based Motivation for Online EM and Combining Hidden Variable Models UAI 2020