Publications

Rishiraj Bhattacharya, Sourav Chakraborty, Yash Pote, Uddalok Sarkar, and Sayantan Sen (2024). Testing Self-Reducible Samplers. In Proceedings of the AAAI Conference on Artificial Intelligenc (AAAI).

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Mohimenul Kabir,, Supratik Chakraborty,, and Kuldeep S. Meel (2024). Exact ASP Counting with Compact Encodings. In Proceedings of AAAI Conference on Artificial Intelligence (AAAI).

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Suwei Yang, and Kuldeep S. Meel (2024). Engineering an Exact Pseudo-Boolean Model Counter. In Proceedings of AAAI Conference on Artificial Intelligence (AAAI).

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Kuldeep S. Meel, Supratik Chakraborty, and S. Akshay (2024). Auditable Algorithms for Approximate Model Counting. In Proceedings of the AAAI Conference on Artificial Intelligenc (AAAI).

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Arijit Shaw, Brendan Juba, and Kuldeep S. Meel (2024). An Approximate Skolem Function Counter. In Proceedings of AAAI Conference on Artificial Intelligence (AAAI).

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Diptarka Chakraborty, Sourav Chakraborty, Gunjan Kumar, and Kuldeep S. Meel (2024). Equivalence Testing: The Power of Bounded Adaptivity. In International Conference on Artificial Intelligence and Statistics (AISTATS).

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Antoine Amarilli, Tim van Bremen, and Kuldeep S. Meel (2024). Conjunctive Queries on Probabilistic Graphs: The Limits of Approximability. In Proceedings of The International Conference on Database Theoryn (ICDT).

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Priyanka Golia (2023). Functional Synthesis via Formal Methods and Machine Learning. PhD Thesis, National University of Singapore and Indian Institute of Technology Kanpur.

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Bishwamittra Ghosh (2023). Interpretability and Fairness in Machine Learning: A Formal Methods Approach. PhD Thesis, National University of Singapore.

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Mohimenul Kabir, and Kuldeep S. Meel (2023). A Fast and Accurate ASP Counting Based Network Reliability Estimator. In Proceedings of International Conference on Logic for Programming, Artificial Intelligence and Reasoning (LPAR).

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Diptarka Chakraborty, Gunjan Kumar, and Kuldeep S. Meel (2023). Support Size Estimation: The Power of Conditioning. In International Symposium on Mathematical Foundations of Computer Science (MFCS).

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Diptarka Chakraborty, Sourav Chakraborty, Gunjan Kumar, and Kuldeep S. Meel (2023). Approximate Model Counting: Is SAT Oracle More Powerful than NP Oracle?. In Proceedings of International Colloquium on Automata, Languages and Programming (ICALP).

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Anna Latour, Arunabha Sen, and Kuldeep S. Meel (2023). Solving the Identifying Code Set Problem with Grouped Independent Support. In Proceedings of the 32nd International Joint Conference on Artificial Intelligence (IJCAI23).

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Arnab Bhattacharyya, Sutanu Gayen, Kuldeep S. Meel, Dimitrios Myrisiotis, Pavan A., and N. V. Vinodchandran (2023). On Approximating Total Variation Distance. In Proceedings of the 32nd International Joint Conference on Artificial Intelligence (IJCAI23).

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Jiong Yang, and Kuldeep S. Meel (2023). Rounding Meets Approximate Model Counting. In Proceedings of International Conference on Computer-Aided Verification (CAV).

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Jiong Yang, Arijit Shaw, Teodora Baluta, Mate Soos, and Kuldeep S. Meel (2023). Explaining SAT Solving Using Causal Reasoning. In Proceedings of International Conference on Theory and Applications of Satisfiability Testing (SAT).

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Tim van Bremen, and Kuldeep S. Meel (2023). Probabilistic Query Evaluation: The Combined FPRAS Landscape. In ACM Symposium on Principles of Database Systems (PODS).

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Paulius Dilkas, and Vaishak Belle (2023). Synthesising Recursive Functions for First-Order Model Counting: Challenges, Progress, and Conjectures. In Proceedings of the International Conference on Principles of Knowledge Representation and Reasoning (KR).

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Suwei Yang, Victor C. Liang, and Kuldeep S. Meel (2023). Scalable Probabilistic Routes. In Proceedings of International Conference on Logic for Programming, Artificial Intelligence and Reasoning (LPAR).

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Bishwamittra Ghosh, Debabrota Basu, and Kuldeep S. Meel (2023). How Biased are Your Features?: Computing Fairness Influence Functions with Global Sensitivity Analysis. In Proceedings of FAccT.

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Paulius Dilkas (2023). Generating Random Instances of Weighted Model Counting: An Empirical Analysis with Varying Primal Treewidth. In Proceedings of Integration of Constraint Programming, Artificial Intelligence, and Operations Research (CPAIOR).

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Yacine Izza, Alexey Ignatiev, and Joao Marques-Silva (2023). On Tackling Explanation Redundancy in Decision Trees. In Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI).

Priyanka Golia, Subhajit Roy, and Kuldeep S. Meel (2023). Synthesis with Explicit Dependencies. In Proceedings of Design, Automation and Test in Europe Conference (DATE).

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Yacine Izza, Xuanxiang Huang, Alexey Ignatiev, Nina Narodytska, Martin C. Cooper, and Joao Marques-Silva (2023). On computing probabilistic abductive explanations. In Int. J. Approx. Reason. (IJAR).

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Xuanxiang Huang, Yacine Izza, and Joao Marques-Silva (2023). Solving Explainability Queries with Quantification: The Case of Feature Relevancy. In Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, (AAAI).

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Ansuman Banerjee, Shayak Chakraborty, Sourav Chakraborty, Kuldeep S. Meel, Uddalok Sarkar, and Sayantan Sen (2023). Testing of Horn Samplers. In International Conference on Artificial Intelligence and Statistics (AISTATS).

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Yong Lai, Kuldeep S. Meel, and Roland Yap (2023). Fast Converging Anytime Model Counting. In Proceedings of the 37th AAAI Conference on Artificial Intelligence (AAAI23).

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A. Pavan, Kuldeep S. Meel, N. V. Vinodchandran, and Arnab Bhattacharyya (2023). Constraint Optimization over Semirings. In Proceedings of the 37th AAAI Conference on Artificial Intelligence (AAAI23).

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Yash Pote, and Kuldeep S. Meel (2022). On Scalable Testing of Samplers. In Advances in Neural Information Processing Systems (NeurIPS).

Bishwamittra Ghosh, Dmitry Malioutov, and Kuldeep S. Meel (2022). Efficient Learning of Interpretable Classification Rules. In Proceedings of JAIR.

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Suwei Yang, Victor Liang, and Kuldeep S. Meel (2022). INC: A Scalable Incremental Weighted Sampler. In Proceedings of Formal Methods in Computer-Aided Design (FMCAD).

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Jiong Yang, Supratik Chakraborty, and Kuldeep S. Meel (2022). Projected Model Counting: Beyond Independent Support. In International Symposium on Automated Technology for Verification and Analysis (ATVA).

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Sourav Chakraborty, N. V. Vinodchandran, and Kuldeep S. Meel (2022). Distinct Elements in Streams: An Algorithm for the (Text) Book. In Proceedings of European Symposium of Algorithms (ESA).

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Kuldeep S. Meel (2022). Counting, Sampling, and Synthesis: The Quest for Scalability. In Proceedings of the 31st International Joint Conference on Artificial Intelligence (IJCAI22).

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Remi Delannoy and Kuldeep S. Meel (2022). On Almost-Uniform Generation of SAT Solutions: The power of 3-wise independent hashing. In Proceedings of Logic in Computer science (LICS).

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Kuldeep S. Meel, Sourav Chakraborty, and N.V. Vinodchandran (2022). Estimation of the Size of Union of Delphic Sets: Achieving Independence from Stream Size. In ACM Symposium on Principles of Database Systems (PODS).

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Mohimenul Kabir, Flavio Everardo, Ankit Shukla, Johannes K. Fichte, Markus Hecher, and Kuldeep S. Meel (2022). ApproxASP – A Scalable Approximate Answer Set Counter. In Proceedings of AAAI Conference on Artificial Intelligence (AAAI).

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Bishwamittra Ghosh, Debabrota Basu, and Kuldeep S. Meel (2022). Algorithmic Fairness Verification with Graphical Models. In Proceedings of AAAI Conference on Artificial Intelligence (AAAI).

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A. Pavan, N. V. Vinodchandran, Arnab Bhattacharyya, and Kuldeep S. Meel (2022). Model Counting Meets Distinct Elements in a Data Stream. In SIGMOD Record.

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Mate Soos, Priyanka Golia, Sourav Chakraborty, and Kuldeep S. Meel (2022). On Quantitative Testing of Samplers. In Proceedings of International Conference on Constraint Programming (CP).

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Priyanka Golia, Brendan Juba, and Kuldeep S. Meel (2022). A Scalable Shannon Entropy Estimator. In Proceedings of 34nd International Conference on Computer-Aided Verification (CAV).

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Eduard Baranov, Sourav Chakraborty, Axel Legay, Kuldeep S. Meel, and N.V. Vinodchandran (2022). A Scalable t-wise Coverage Estimator. In Proceedings of International Conference on Software Engineering (ICSE).

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Aditya Shrotri, Nina Narodytska, Alexey Ignatiev, Kuldeep S. Meel, Joao Marques-Silva, and Moshe Y. Vardi (2022). Constraint-Driven Explanations of Black-Box ML Models. In Proceedings of AAAI Conference on Artificial Intelligence (AAAI).

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Mate Soos, and Kuldeep S. Meel (2021). Gaussian Elimination Meets Maximum Satisfiability. In Proceedings of the International Conference on Principles of Knowledge Representation and Reasoning (KR).

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Yash Pote, and Kuldeep S. Meel (2021). Testing Probabilistic Circuits. In Advances in Neural Information Processing Systems (NeurIPS).

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Jiong Yang, and Kuldeep S. Meel (2021). Engineering an Efficient PB-XOR Solver. In Proceedings of International Conference on Constraint Programming (CP).

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Priyanka Golia, Dror Fried, Subhajit Roy, and Kuldeep S. Meel (2021). Engineering an Efficient Boolean Functional Synthesis Engine. In Proceedings of International Conference On Computer Aided Design (ICCAD).

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Priyanka Golia, Mate Soos, Sourav Chakraborty, and Kuldeep S. Meel (2021). Designing Samplers is Easy: The Boon of Testers. In Proceedings of Formal Methods in Computer-Aided Design (FMCAD).

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Durgesh Agrawal, Yash Pote, and Kuldeep S. Meel (2021). Partition Function Estimation: A Quantitative Study. In Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI).

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Gilles Pesant, Kuldeep S. Meel, and Mahshid Mohammadalitajrishi (2021). On the Usefulness of Linear Modular Arithmetic in Constraint Programming. In Proceedings of International Conference on the Integration of Constraint Programming, Artificial Intelligence, and Operations Research (CPAIOR).

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Nicolas Prevot, Mate Soos, and Kuldeep S. Meel (2021). Leveraging GPUs for Effective Clause Sharing in Parallel SAT Solving. In Proceedings of the International Conference on Theory and Applications of Satisfiability Testing (SAT), 2021..

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Jaroslav Bendík, and Kuldeep S. Meel (2021). Counting Minimal Unsatisfiable Subsets. In Proceedings of International Conference on Computer-Aided Verification (CAV).

Priyanka Golia, Subhajit Roy, and Kuldeep S. Meel (2021). Program Synthesis as Dependency Quantified Formula Modulo Theory. In Proceedings International Joint Conference on Artificial Intelligence (IJCAI).

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Arnab Bhattacharyya, Kuldeep S. Meel, A. Pavan, and N.V. Vinodchandran (2021). Model Counting meets F0 Estimation. In ACM Symposium on Principles of Database Systems (PODS).

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Kuldeep S. Meel, N.V. Vinodchandran, and Sourav Chakraborty (2021). Estimating the Size of Unions of Sets in Streaming Models. In ACM Symposium on Principles of Database Systems (PODS).

Teodora Baluta, Zheng Leong Chua, Kuldeep S. Meel, and Prateek Saxena (2021). Scalable Quantitative Verification For Deep Neural Networks. In IEEE/ACM 43rd International Conference on Software Engineering (ICSE).

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Yong Lai, Kuldeep S. Meel, and Roland Yap (2021). The Power of Literal Equivalence in Model Counting. In Proceedings of AAAI Conference on Artificial Intelligence (AAAI).

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Tim van Bremen, Vincent Derkinderen, Shubham Sharma, Subhajit Roy, and Kuldeep S. Meel (2021). Symmetric Component Caching for Model Counting on Structured Instances. In Proceedings of AAAI Conference on Artificial Intelligence (AAAI).

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Suwei Yang, Massimo Lupascu, and Kuldeep S. Meel (2021). Predicting Forest Fire Using Remote Sensing Data And Machine Learning. In Proceedings of AAAI Conference on Artificial Intelligence (AAAI).

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Bishwamittra Ghosh, Debabrota Basu, and Kuldeep S. Meel (2021). Justicia A Stochastic SAT Approach to Formally Verify Fairness. In Proceedings of AAAI Conference on Artificial Intelligence (AAAI).

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Jaroslav Bendík, and Kuldeep S. Meel (2021). Counting Maximal Satisfiable Subsets. In Proceedings of AAAI Conference on Artificial Intelligence (AAAI).

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Eduard Baranov, Axel Legay, and Kuldeep S. Meel (2020). Baital: An Adaptive Weighted Sampling Approach for Improved t-wise Coverage. In Proceedings of the 28th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE).

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Jeffrey M. Dudek, Dror Fried, and Kuldeep S. Meel (2020). Taming Discrete Integration via the Boon of Dimensionality. In Advances in Neural Information Processing Systems (NeurIPS).

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Kuldeep S. Meel, Yash Pote, and Sourav Chakraborty (2020). On Testing of Samplers. In Advances in Neural Information Processing Systems (NeurIPS).

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Arnab Bhattacharyya, Sutanu Gayen, Kuldeep S. Meel, and N. V. Vinodchandran (2020). Efficient Distance Approximation for Structured High-Dimensional Distributions via Learning. In Advances in Neural Information Processing Systems (NeurIPS).

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Rahul Gupta, Subhajit Roy, and Kuldeep S. Meel (2020). Phase Transition Behaviour in Knowledge Compilation. In Proceedings of International Conference on Constraint Programming (CP).

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Durgesh Agrawal, Bhavishya, and Kuldeep S. Meel (2020). On the Sparsity of XORs in Approximate Model Counting. In Proceedings of the International Conference on Theory and Applications of Satisfiability Testing (SAT).

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Arijit Shaw, and Kuldeep S. Meel (2020). Designing New Phase Selection Heuristics. In Proceedings of the International Conference on Theory and Applications of Satisfiability Testing (SAT).

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Kuldeep S. Meel ⓡ S. Akshay (2020). Sparse Hashing for Scalable Approximate Model Counting: Theory and Practice. In Proceedings of Logic in Computer science (LICS).

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Mate Soos, Stephan Gocht, and Kuldeep S. Meel (2020). Tinted, Detached, and Lazy CNF-XOR solving and its Applications to Counting and Sampling. In Proceedings of 32nd International Conference on Computer-Aided Verification (CAV).

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Priyanka Golia, Subhajit Roy, and Kuldeep S. Meel (2020). Manthan: A Data-Driven Approach for Boolean Function Synthesis. In Proceedings of 32nd International Conference on Computer-Aided Verification (CAV).

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Jaroslav Bendík, and Kuldeep S. Meel (2020). Approximate Counting of Minimal Unsatisfiable Subsets. In Proceedings of 32nd International Conference on Computer-Aided Verification (CAV).

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A. Dileep, Kuldeep S. Meel, and Ammar F. Sabili (2020). Induction Models on N. In Proceedings of International Conference on Logic for Programming Artificial Intelligence and Reasoning (LPAR).

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Wenxi Wang, Muhammad Usman, Alyas Almaawi, Kaiyuan Wang, Kuldeep S. Meel, and Sarfraz Khurshid (2020). A Study of Symmetry Breaking Predicates and Model Counting. In Proceedings of Tools and Algorithms for the Construction and Analysis of Systems (TACAS).

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Bishwamittra Ghosh, Dmitry Malioutov, and Kuldeep S. Meel (2020). Classification Rules in Relaxed Logical Form. In Proceedings of ECAI.

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Lorenzo Ciampiconi, Bishwamittra Ghosh, Jonathan Scarlett, and Kuldeep S. Meel (2020). A MaxSAT-based Framework for Group Testing. In Proceedings of AAAI Conference on Artificial Intelligence (AAAI).

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Yaqi Xie, Ziwei Xu, Mohan S. Kankanhalli, Kuldeep S. Meel, and Harold Soh (2019). Embedding Symbolic Knowledge into Deep Networks . In Advances in Neural Information Processing Systems(NeurIPS).

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Teodora Baluta, Shiqi Shen, Shweta Shinde, Kuldeep S. Meel, and Prateek Saxena (2019). Quantitative Verification of Neural Networks And Its Security Applications . In Proceedings of the 2019 ACM Conference on Computer and Communications Security (CCS).

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Alexis de Colnet, and Kuldeep S. Meel (2019). Dual Hashing-based Algorithms for Discrete Integration . In Proceedings of International Conference on Constraint Programming (CP).

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Roger Paredes, Leonardo Duenas-Osorio, Kuldeep S. Meel, and Moshe Y. Vardi (2019). Network Reliability Estimation in Theory and Practice . Journal of Reliability Engineering and System Safety(RESS).

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Shubham Sharma, Subhajit Roy, Mate Soos, and Kuldeep S. Meel (2019). GANAK: A Scalable Probabilistic Exact Model Counter. In Proceedings International Joint Conference on Artificial Intelligence (IJCAI).

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Yash Pote, Saurabh Joshi, and Kuldeep S. Meel (2019). Phase Transition Behavior of Cardinality and XOR Constraints . In Proceedings of International Joint Conference on Artificial Intelligence (IJCAI).

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Kuldeep S. Meel, Aditya A. Shrotri, and Moshe Y. Vardi (2019). Not All FPRASs are Equal: Demystifying FPRASs for DNF-Counting (Extended Abstract) . In Proceedings of International Joint Conference on Artificial Intelligence (IJCAI).

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Mate Soos, Raghav Kulkarni, and Kuldeep S. Meel (2019). CrystalBall: Gazing in the Black Box of SAT Solving . In Proceedings of the International Conference on Theory and Applications of Satisfiability Testing (SAT).

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Nina Narodytska, Aditya Shrotri, Kuldeep S. Meel, Alexey Ignatiev, and Joao Marques Silva (2019). Assessing Heuristic Machine Learning Explanations with Model Counting . In Proceedings of the International Conference on Theory and Applications of Satisfiability Testing (SAT).

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Rahul Gupta, Shubham Sharma, Subhajit Roy, and Kuldeep S. Meel (2019). WAPS: Weighted and Projected Sampling . In Proceedings of Tools and Algorithms for the Construction and Analysis of Systems (TACAS).

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Davin Choo,  Mate Soos, Kian Ming A. Chai, and Kuldeep S. Meel (2019). BOSPHORUS: Bridging ANF and CNF Solvers . In Proceedings of Design, Automation, and Test in Europe (DATE).

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Supratik Chakraborty, Kuldeep S. Meel, and Moshe Y. Vardi (2019). On the Hardness of Probabilistic Inference Relaxations. In Proceedings of AAAI Conference on Artificial Intelligence (AAAI).

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Sourav Chakraborty, and Kuldeep S. Meel (2019). On testing of Uniform Samplers . In Proceedings of AAAI Conference on Artificial Intelligence (AAAI).

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Mate Soos, and Kuldeep S. Meel (2019). BIRD: Engineering an Efficient CNF-XOR SAT Solver and its Applications to Approximate Model Counting. In Proceedings of AAAI Conference on Artificial Intelligence (AAAI).

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Bishwamittra Ghosh, and Kuldeep S. Meel (2019). IMLI: An Incremental Framework for MaxSAT-Based Learning of Interpretable Classification Rules . In Proceedings of AAAI/ACM Conference on AI, Ethics, and Society (AIES).

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Kuldeep S. Meel, Aditya A. Shrotri, and Moshe Y. Vardi (2018). Not All FPRASs are Equal: Demystifying FPRASs for DNF-Counting . In Proceedings of International Conference on Constraint Programming (CP).

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Shubham Sharma, Rahul Gupta, Subhajit Roy, and Kuldeep S. Meel (2018). Knowledge Compilation meets Uniform Sampling. In Proceedings of International Conference on Logic for Programming Artificial Intelligence and Reasoning (LPAR).

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Dmitry Malioutov, and Kuldeep S. Meel (2018). MLIC: A MaxSAT-Based framework for learning interpretable classification rules. In Proceedings of International Conference on Constraint Programming (CP).

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Fabrizio Biondi, Michael Enescu, Annelie Heuser, Axel Legay, Kuldeep S. Meel, and Jean Quilbeuf (2018). Scalable Approximation of Quantitative Information Flow in Programs. In Proceedings of International Conference on Verification, Model Checking, and Abstract Interpretation.

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Kuldeep S. Meel, Aditya A. Shrotri, and Moshe Y. Vardi (2017). On Hashing-Based Approaches to Approximate DNF-Counting . In Proceedings of IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science.

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Kuldeep S. Meel (2017). Constrained Counting and Sampling: Bridging the Gap between Theory and Practice . PhD Thesis, Rice University.

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Jeffrey Dudek, Kuldeep S. Meel, and Moshe Y. Vardi (2017). The Hard Problems Are Almost Everywhere For Random CNF-XOR Formulas . In Proceedings of International Joint Conference on Artificial Intelligence (IJCAI).

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Leonardo Duenas-Osorio, Kuldeep S. Meel, Roger Paredes, and Moshe Y. Vardi (2017). Counting-Based Reliability Estimation for Power-Transmission Grids. In Proceedings of AAAI Conference on Artificial Intelligence (AAAI).

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Alexander Ivrii, Sharad Malik, Kuldeep S. Meel, and Moshe Y. Vardi (2016). On Computing Minimal Independent Support and Its Applications to Sampling and Counting . Constraints 21(1).

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Jeffrey Dudek, Kuldeep S. Meel, and Moshe Y. Vardi (2016). Combining the k-CNF and XOR Phase-Transitions . In Proceedings of International Joint Conference on Artificial Intelligence (IJCAI).

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Supratik Chakraborty, Kuldeep S. Meel, and Moshe Y. Vardi (2016). Algorithmic Improvements in Approximate Counting for Probabilistic Inference: From Linear to Logarithmic SAT Calls . In Proceedings of International Joint Conference on Artificial Intelligence (IJCAI).

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Supratik Chakraborty, Kuldeep S. Meel, Rakesh Mistry, and Moshe Y. Vardi (2016). Approximate Probabilistic Inference via Word-Level Counting . In Proceedings of AAAI Conference on Artificial Intelligence (AAAI).

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Deepak Majeti, Kuldeep S. Meel, Raj Barik, and Vivek Sarkar (2016). Automatic Data Layout Generation and Kernel Mapping for CPU+GPU Architectures . In Proceedings of International Conference on Compiler Construction (CC).

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Kuldeep S. Meel, Moshe Y. Vardi, Supratik Chakraborty, Daniel J. Fremont, Sanjit A. Seshia, Dror Fried, Alexander Ivrii, and Sharad Malik (2016). Constrained Sampling and Counting: Universal Hashing meets SAT Solving. In Proceedings of Workshop on Beyond NP(BNP).

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Karthik, Murthy, Sri Raj, Paul, Kuldeep S. Meel, Tiago Cogumbreiro, and John Mellor-Crummey (2016). Design and Verification of Distributed Phasers. In Proceedings of International European Conference on Parallel and Distributed Computing (Euro-Par).

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Alexander Ivrii, Sharad Malik, Kuldeep S. Meel, and Moshe Y. Vardi (2015). On Computing Minimal Independent Support and Its Applications to Sampling and Counting . In Proceedings of International Conference on Constraint Programming (CP).

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Supratik Chakraborty, Dror Fried, Kuldeep S. Meel, and Moshe Y. Vardi (2015). From Weighted to Unweighted Model Counting . In Proceedings of International Joint Conference on Artificial Intelligence (IJCAI).

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Supratik Chakraborty, Daniel J. Fremont, Kuldeep S. Meel, Sanjit A. Seshia, and Moshe Y. Vardi (2015). On Parallel Scalable Uniform SAT Witness Generator. In Proceedings of Tools and Algorithms for the Construction and Analysis of Systems (TACAS).

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Deepak Majeti, Kuldeep S. Meel, Raj Barik, and Vivek Sarkar (2014). ADHA: Automatic Data layout framework for Heterogeneous Architectures. In Proceedings of Parallel Architecture and Compilation Techniques (PACT).

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Supratik Chakraborty, Daniel J. Fremont, Kuldeep S. Meel, Sanjit A. Seshia, and Moshe Y. Vardi (2014). Distribution-Aware Sampling and Weighted Model Counting for SAT. In Proceedings of AAAI Conference on Artificial Intelligence (AAAI).

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Supratik Chakraborty, Kuldeep S. Meel, and Moshe Y. Vardi (2014). Balancing Scalability and Uniformity in SAT-Witness Generator . In Proceedings of Design Automation Conference (DAC).

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Supratik Chakraborty, Kuldeep S. Meel, and Moshe Y. Vardi (2013). A Scalable Approximate Model Counter . In Proceedings of International Conference on Constraint Programming (CP).

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Supratik Chakraborty, Kuldeep S. Meel, and Moshe Y. Vardi (2013). A Scalable and Nearly Uniform Generator of SAT Witnesses. In Proceedings of International Conference on Computer-Aided Verification (CAV).

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