Probabilistic Modeling

Approximating bounded tree-width Bayesian network classifiers with OBDD PGM 2020 A Programmatic and Semantic Approach to Explaining and Debugging Neural Network Based Object Detectors CVPR 2020 A Score-and-Search Approach to Learning Bayesian Networks with Noisy-OR Relations PGM 2020 ASR-Free Pronunciation Assessment Interspeech 2020 A Variational Point Process Model for Social Event Sequences AAAI 2020 Bayesian Adversarial Human Motion Synthesis CVPR 2020 Bayesian Network Model Averaging Classifiers by Subbagging PGM 2020 Bean Machine: A Declarative Probabilistic Programming Language For Efficient Programmable Inference PGM 2020 Belief Merging Operators as Maximum Likelihood Estimators IJCAI 2020 Beyond the Grounding Bottleneck: Datalog Techniques for Inference in Probabilistic Logic Programs AAAI 2020 Bootstrapping neural processes NeurIPS 2020 Building Causal Interaction Models by Recursive Unfolding PGM 2020 Censored Quantile Regression Forest AISTATS 2020 Community-Based Group Graphical Lasso JMLR 2020 Conditional Sum-Product Networks: Imposing Structure on Deep Probabilistic Architectures PGM 2020 Conditioning and Processing: Techniques to Improve Information-Theoretic Generalization Bounds NeurIPS 2020 Constructing a Chain Event Graph from a Staged Tree PGM 2020 Contrastive Divergence Learning with Chained Belief Propagation PGM 2020 Co-Occurrence Estimation from Aggregated Data with Auxiliary Information AAAI 2020 Correlated Equilibria for Approximate Variational Inference in MRFs PGM 2020 CREMA: A Java Library for Credal Network Inference PGM 2020 Data Uncertainty Learning in Face Recognition CVPR 2020 Deep Gaussian Markov Random Fields ICML 2020 Deep Generalized Convolutional Sum-Product Networks PGM 2020 Deep Graph Pose: a semi-supervised deep graphical model for improved animal pose tracking NeurIPS 2020