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Explanation-Based Approximate Weighted Model Counting for Probabilistic Logics.

, , , and . AAAI, page 2490-2496. AAAI Press, (2014)

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Query Processing on Probabilistic Data: A Survey., and . Found. Trends Databases, 7 (3-4): 197-341 (2017)Lifted Relax, Compensate and then Recover: From Approximate to Exact Lifted Probabilistic Inference., , and . UAI, page 131-141. AUAI Press, (2012)Tractable computation of expected kernels., , , and . UAI, volume 161 of Proceedings of Machine Learning Research, page 1163-1173. AUAI Press, (2021)Probabilistic Program Abstractions., , and . UAI, AUAI Press, (2017)Semantic Probabilistic Layers for Neuro-Symbolic Learning., , , , and . NeSy, volume 3432 of CEUR Workshop Proceedings, page 413. CEUR-WS.org, (2023)Liftability of Probabilistic Inference: Upper and Lower Bounds., and . StarAI@UAI, (2012)PYLON: A PyTorch Framework for Learning with Constraints., , , , , , , , and . AAAI, page 13152-13154. AAAI Press, (2022)Reports of the AAAI 2014 Conference Workshops, , , , , , , , , and 24 other author(s). AI Magazine, 36 (1): 87--98 (2015)Skolemization for Weighted First-Order Model Counting, , and . Proceedings of the 14th International Conference on Principles of Knowledge Representation and Reasoning: Proceedings (KR), (2014)Lifted Variable Elimination: A Novel Operator and Completeness Results, , , , and . CoRR, (2012)