Hei Chan and Adnan Darwiche. Reasoning About Bayesian Network Classifiers. In Proceedings of the 19th Conference on Uncertainty in Artificial Intelligence (UAI), 2003. pdf
Andy Shih and Arthur Choi and Adnan Darwiche. A Symbolic Approach to Explaining Bayesian Network. In Proceedings of the 27th International Joint Conference on Artificial Intelligence (IJCAI), 2018. pdf
Andy Shih and Arthur Choi and Adnan Darwiche. Formal Verification of Bayesian Network Classifiers. In Proceedings of the 9th International Conference on Probabilistic Graphical Models (PGM), 2018. pdf
Andy Shih and Arthur Choi and Adnan Darwiche. Compiling Bayesian Networks into Decision Graphs. In Proceedings of the 33rd AAAI Conference on Artificial Intelligence (AAAI), 2019. pdf
Arthur Choi and Weijia Shi and Andy Shih and Adnan Darwiche. Compiling Neural Networks into Tractable Boolean Circuits. Presented at the AAAI Spring Symposium on Verification of Neural Networks (VNN), 2019. pdf
Andy Shih and Adnan Darwiche and Arthur Choi. Verifying Binarized Neural Networks by Local Automaton Learning (workshop version). Presented at the AAAI Spring Symposium on Verification of Neural Networks (VNN), 2019. pdf
Andy Shih and Adnan Darwiche and Arthur Choi. Verifying Binarized Neural Networks by Angluin-Style Learning. To appear in Proceedings of the 22nd International Conference on Theory and Applications of Satisfiability Testing (SAT), 2019. pdf
BNC_SDD: a compiler for converting a Bayesian network classifier into a Sentential Decision Diagram. github
RF_SDD: a software for learning a Random Forest classifier, and then compiling it into a Sentential Decision Diagram. github
STEP: Symbolic and Tractable Explanation Package - a package for running explanations on Sentential Decision Diagrams. github (in progress)
CNF_OBDD: a compiler for converting a CNF into an OBDD using the L* learning algorithm. github (in progress)