probabilistic inference

Matrix Product States for Inference in Discrete Probabilistic Models JMLR 2021 Noise as a Resource for Learning in Knowledge Distillation WACV 2021 On Solving Probabilistic Linear Diophantine Equations JMLR 2021 On the Complexity of Sum-of-Products Problems over Semirings AAAI 2021 Probabilistic DAG search UAI 2021 PSD Representations for Effective Probability Models NeurIPS 2021 Semantic Linking Maps for Active Visual Object Search (Extended Abstract) IJCAI 2021 Weighted model counting with conditional weights for Bayesian networks UAI 2021 Ancestral Gumbel-Top-k Sampling for Sampling Without Replacement JMLR 2020 Approximate Inference in Discrete Distributions with Monte Carlo Tree Search and Value Functions AISTATS 2020 Approximate Weighted First-Order Model Counting: Exploiting Fast Approximate Model Counters and Symmetry IJCAI 2020 Bean Machine: A Declarative Probabilistic Programming Language For Efficient Programmable Inference PGM 2020 Beyond the Grounding Bottleneck: Datalog Techniques for Inference in Probabilistic Logic Programs AAAI 2020 CREMA: A Java Library for Credal Network Inference PGM 2020 Deep Generalized Convolutional Sum-Product Networks PGM 2020 Domain Knowledge Empowered Structured Neural Net for End-to-End Event Temporal Relation Extraction EMNLP 2020 Efficient semidefinite-programming-based inference for binary and multi-class MRFs NeurIPS 2020 Empirical Bounds on Linear Regions of Deep Rectifier Networks AAAI 2020 Factor Graph Grammars NeurIPS 2020 Learning to Reason: Leveraging Neural Networks for Approximate DNF Counting AAAI 2020 Learning Weighted Model Integration Distributions AAAI 2020 Lifted Hybrid Variational Inference IJCAI 2020 Lower Bounds for Approximate Knowledge Compilation IJCAI 2020 Making Sense of Reinforcement Learning and Probabilistic Inference ICLR 2020 OCEAN: Online Task Inference for Compositional Tasks with Context Adaptation UAI 2020