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Probabilistic Task-Adaptive Graph Rewiring

C. Qian, A. Manolache, K. Ahmed, Z. Zeng, G. den Broeck, M. Niepert, and C. Morris. ICML 2023 Workshop on Differentiable Almost Everything: Differentiable Relaxations, Algorithms, Operators, and Simulators, (2023)

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Nina van den Daele University of Stuttgart

Michaela Denzel University of Stuttgart

Jan Denzel University of Stuttgart

Dr. phil. Leo van Waveren University of Stuttgart

Dr. Thijs van Westen University of Stuttgart

Other publications of authors with the same name

Skolemization for Weighted First-Order Model Counting.G. den Broeck, W. Meert, and A. Darwiche. KR, AAAI Press, (2014)Tractable Learning for Complex Probability Queries.J. Bekker, J. Davis, A. Choi, A. Darwiche, and G. den Broeck. NIPS, page 2242-2250. (2015)Lifted Variable Elimination: A Novel Operator and Completeness ResultsN. Taghipour, D. Fierens, G. den Broeck, J. Davis, and H. Blockeel. CoRR, (2012)A Semantic Loss Function for Deep Learning with Symbolic Knowledge.J. Xu, Z. Zhang, T. Friedman, Y. Liang, and G. den Broeck. CoRR, (2017)On the Complexity and Approximation of Binary Evidence in Lifted Inference.G. den Broeck, and A. Darwiche. CoRR, (2013)Probabilistic Program Abstractions.S. Holtzen, T. Millstein, and G. den Broeck. CoRR, (2017)Lifted Relax, Compensate and then Recover: From Approximate to Exact Lifted Probabilistic InferenceG. den Broeck, A. Choi, and A. Darwiche. CoRR, (2012)Open-World Probabilistic Databases: An Abridged Report.I. Ceylan, A. Darwiche, and G. den Broeck. IJCAI, page 4796-4800. ijcai.org, (2017)Optimal Feature Selection for Decision Robustness in Bayesian Networks.Y. Choi, A. Darwiche, and G. den Broeck. IJCAI, page 1554-1560. ijcai.org, (2017)Hashing-Based Approximate Probabilistic Inference in Hybrid Domains: An Abridged Report.V. Belle, G. den Broeck, and A. Passerini. IJCAI, page 4115-4119. IJCAI/AAAI Press, (2016)