Publications

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Counting

On the smallest antichain that generates an ideal of a given size
L. Sunil Chandran, Rishikesh Gajjala and Kuldeep S. Meel.
Journal of Combinatorial Theory, Series A, 222:106182, 2026.
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Counting and Sampling Traces in Regular Languages
Alexis de Colnet, Kuldeep S. Meel and Umang Mathur.
Proceedings of the ACM on Programming Languages, 10(POPL):2352–2379, 2026.
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On approximability of propositional model counting
Diptarka Chakraborty, Lawqueen Kanesh and Kuldeep S. Meel.
Theoretical Computer Science, 1075:115930, 2026.
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#CFG and #DNNF admit FPRAS.
Kuldeep S. Meel, and Alexis de Colnet.
In Proceedings of the Annual ACM-SIAM Symposium on Discrete Algorithms (SODA) , pp. 5978–6010, 2026.
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Counting Answer Sets of Disjunctive Answer Set Programs
Mohimenul Kabir, Supratik Chakraborty and Kuldeep S. Meel.
Theory and Practice of Logic Programming, 25(4):703–721, September 2025.
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CNFs and DNFs with Exactly k Solutions.
L. Sunil Chandran, Rishikesh Gajjala and Kuldeep S. Meel.
In Proceedings of the International Conference on Theory and Applications of Satisfiability Testing (SAT), pp. 9:1–9:15, August 2025.
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Towards Practical First-Order Model Counting.
Ananth K. Kidambi, Guramrit Singh, Paulius Dilkas and Kuldeep S. Meel.
In Proceedings of the International Conference on Theory and Applications of Satisfiability Testing (SAT), pp. 18:1–18:18, August 2025.
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On Top-Down Pseudo-Boolean Model Counting.
Suwei Yang, Yong Lai and Kuldeep S. Meel.
In Proceedings of the International Conference on Theory and Applications of Satisfiability Testing (SAT), pp. 31:1–31:10, August 2025.
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Panini: An Efficient and Flexible Knowledge Compiler.
Yong Lai, Kuldeep S. Meel and Roland H. C. Yap.
In Proceedings of International Conference on Computer-Aided Verification (CAV), pp. 92–105, July 2025.
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An FPRAS for Model Counting for Non-Deterministic Read-Once Branching Programs .
Kuldeep S. Meel ⓡ Alexis de Colnet.
In Proceedings of the International Conference on Database Theory (ICDT), March 2025.
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Towards Projected and Incremental Pseudo-Boolean Model Counting.
Suwei Yang, and Kuldeep S. Meel.
In Proceedings of AAAI Conference on Artificial Intelligence (AAAI), February 2025.
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Towards Real-Time Approximate Counting.
Yash Pote ⓡ Kuldeep S. Meel ⓡ JIong Yang.
In Proceedings of AAAI Conference on Artificial Intelligence (AAAI), February 2025.
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Approximating Queries on Probabilistic Graphs
Antoine Amarilli, Timothy van Bremen, Octave Gaspard and Kuldeep S. Meel.
Logical Methods in Computer Science, 21(4), 2025.
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Efficient Volume Computation for SMT Formulas.
Arijit Shaw, Uddalok Sarkar and Kuldeep S. Meel.
In Proceedings of International Conference on Knowledge Representation and Reasoning (KR), 2025.
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Rounding meets approximate model counting
Jiong Yang, and Kuldeep S. Meel.
Formal Methods in System Design, 67(2):189–221, 2025.
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Towards Practical FPRAS for #NFA: Exploiting the Power of Dependence
Kuldeep S. Meel, and Alexis de Colnet.
Proceedings of the ACM on Management of Data, 3(2):116:1–116:23, june 2025.
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Engineering an Efficient Probabilistic Exact Model Counter.
Mate Soos, and Kuldeep S. Meel.
In Proceedings of International Conference on Computer-Aided Verification (CAV), pp. 72–91, 2025.
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Scalable Counting of Minimal Trap Spaces and Fixed Points in Boolean Networks .
Mohimenul Kabir, Van-Giang Trinh, Samuel Pastva and Kuldeep S. Meel.
In Proceedings of International Conference on Constraint Programming (CP), pp. 17:1–17:26, 2025.
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Approximate SMT Counting Beyond Discrete Domains.
Arijit Shaw, and Kuldeep S. Meel.
In Proceedings of Design Automation Conference (DAC), pp. 1–7, 2025.
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On Lower Bounding Minimal Model Count.
Mohimenul Kabir, and Kuldeep S. Meel.
In Proceedings of the International Conference on Logic Programming (ICLP), November 2024.
Best Paper Award
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Model Counting in the Wild.
Arijit Shaw, and Kuldeep S. Meel.
In Proceedings of International Conference on Knowledge Representation and Reasoning (KR), November 2024.
Details BibTeX Download: [pdf]

Formally Certified Approximate Model Counting.
Yong Kiam Tan, Jiong Yang, Mate Soos, Magnus O. Myreen and Kuldeep S. Meel.
In Proceedings of International Conference on Computer-Aided Verification (CAV), July 2024.
Distinguished Paper Award
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Engineering an Efficient Preprocessor for Model Counting.
Mate Soos, and Kuldeep S. Meel.
In Proceedings of Design Automation Conference (DAC), June 2024.
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A faster FPRAS for #NFA.
Kuldeep S. Meel, Sourav Chakraborty and Umang Mathur.
In Proceedings of ACM Symposium on Principles of Database Systems (PODS), June 2024.
Details BibTeX Download: [pdf]

Auditable Algorithms for Approximate Model Counting.
Kuldeep S. Meel, Supratik Chakraborty and S. Akshay.
In Proceedings of AAAI Conference on Artificial Intelligence (AAAI), January 2024.
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Exact ASP Counting with Compact Encodings.
Mohimenul Kabir, Supratik Chakraborty and Kuldeep S. Meel.
In Proceedings of AAAI Conference on Artificial Intelligence (AAAI), January 2024.
Details BibTeX Download: [pdf]

Engineering an Exact Pseudo-Boolean Model Counter.
Suwei Yang, and Kuldeep S. Meel.
In Proceedings of AAAI Conference on Artificial Intelligence (AAAI), January 2024.
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An Approximate Skolem Function Counter.
Arijit Shaw, Brendan Juba and Kuldeep S. Meel.
In Proceedings of AAAI Conference on Artificial Intelligence (AAAI), January 2024.
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Engineering an Efficient Approximate DNF-Counter.
Mate Soos, Divesh Aggarwal, Sourav Chakraborty, Kuldeep S. Meel and Maciej Obremski.
In Proceedings of International Joint Conference on Artificial Intelligence (IJCAI), August 2023.
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Rounding meets Approximate Model Counting.
Jiong Yang, and Kuldeep S. Meel.
In Proceedings of International Conference on Computer-Aided Verification (CAV), July 2023.
Distinguished Paper Award
Details BibTeX Download: [pdf]

Approximate Model Counting: Is SAT Oracle More Powerful than NP Oracle? .
Diptarka Chakraborty, Sourav Chakraborty, Gunjan Kumar and Kuldeep S. Meel.
In Proceedings of EATCS International Colloquium on Automata, Languages and Programming (ICALP), July 2023.
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A Fast and Accurate ASP Counting Based Network Reliability Estimator.
Mohimenul Kabir, and Kuldeep S. Meel.
In Proceedings of International Conference on Logic for Programming Artificial Intelligence and Reasoning (LPAR), June 2023.
Details BibTeX Download: [pdf]

Probabilistic Query Evaluation: the Combined FPRAS Landscape.
Timothy van Bremen, and Kuldeep S. Meel.
In Proceedings of ACM Symposium on Principles of Database Systems (PODS), June 2023.
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Fast Converging Anytime Model Counting.
Yong Lai, Kuldeep S. Meel and Roland Yap.
In Proceedings of AAAI Conference on Artificial Intelligence (AAAI), January 2023.
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Arjun: An Efficient Independent Support Computation Technique and its Applications to Counting and Sampling .
Mate Soos, and Kuldeep S. Meel.
In Proceedings of IEEE/ACM International Conference on Computer-Aided Design (ICCAD), November 2022.
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Projected Model Counting: Beyond Independent Support.
Jiong Yang, Supratik Chakraborty and Kuldeep S. Meel.
In Proceedings of International Symposium on Automated Technology for Verification and Analysis (ATVA), October 2022.
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Counting, Sampling, and Synthesis: The Quest for Scalability.
Kuldeep S. Meel.
In Proceedings of International Joint Conference on Artificial Intelligence (IJCAI), July 2022.
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Model Counting Meets Distinct Elements in a Data Stream
A. Pavan, N. V. Vinodchandran, Arnab Bhattacharyya and Kuldeep S. Meel .
SIGMOD Record, 51(1):87–94, June 2022.
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ApproxASP - A Scalable Approximate Answer Set Counter.
Mohimenul Kabir, Flavio Everardo, Ankit K. Shukla, Markus Hecher, Johannes Fichte and Kuldeep S. Meel.
In Proceedings of AAAI Conference on Artificial Intelligence (AAAI), February 2022.
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Partition Function Estimation: A Quantitative Study.
Durgesh Agrawal, Yash Pote and Kuldeep S. Meel.
In Proceedings of International Joint Conference on Artificial Intelligence (IJCAI), August 2021.
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Counting Minimal Unsatisfiable Subsets.
Jaroslav Bendik, and Kuldeep S. Meel.
In Proceedings of International Conference on Computer-Aided Verification (CAV), July 2021.
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On the Usefulness of Linear Modular Arithmetic in Constraint Programming .
Gilles Pesant, Kuldeep S. Meel and Mahshid Mohammadalitajrishi.
In Proceedings of International Conference on the Integration of Constraint Programming, Artificial Intelligence, and Operations Research (CPAIOR), July 2021.
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Model Counting meets F0 Estimation.
A. Pavan ⓡ N.V. Vinodchandran ⓡ Arnab Bhattacharya ⓡ Kuldeep S. Meel.
In Proceedings of ACM Symposium on Principles of Database Systems (PODS), June 2021.
CACM Research Highlight and 2021 ACM SIGMOD Research Highlight
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The Power of Literal Equivalence in Model Counting.
Yong Lai, Kuldeep S. Meel and Roland Yap.
In Proceedings of AAAI Conference on Artificial Intelligence (AAAI), February 2021.
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Symmetric Component Caching for Model Counting on Combinatorial Instances .
Timothy van Bremen, Vincent Derkinderen, Shubham Sharma, Subhajit Roy and Kuldeep S. Meel .
In Proceedings of AAAI Conference on Artificial Intelligence (AAAI), February 2021.
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Counting Maximal Satisfiable Subsets.
Jaroslav Bendik, and Kuldeep S. Meel.
In Proceedings of AAAI Conference on Artificial Intelligence (AAAI), February 2021.
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Approximate Model Counting.
Supratik Chakraborty, Kuldeep S. Meel and Moshe Y. Vardi .
In Armin Biere, Marijn Heule, Hans van Maaren and Toby Walsh , editors, Handbook of Satisfiability - Second Edition, Frontiers in Artificial Intelligence and Applications, pp. 1015–1045, IOS Press, 2021.
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Taming Discrete Integration via the Boon of Dimensionality.
Jeffrey M. Dudek, Dror Fried and Kuldeep S. Meel.
In Proceedings of Advances in Neural Information Processing Systems(NeurIPS), December 2020.
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Sparse Hashing for Scalable Approximate Model Counting: Theory and Practice .
Kuldeep S. Meel ⓡ Akshay,S..
In Proceedings of Logic in Computer science (LICS), July 2020.
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On the Sparsity of XORs in Approximate Model Counting.
Durgesh Agrawal, Bhavishya and Kuldeep S. Meel.
In Proceedings of the International Conference on Theory and Applications of Satisfiability Testing (SAT), July 2020.
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Tinted, Detached, and Lazy CNF-XOR solving and its Applications to Counting and Sampling .
Mate Soos, Stephan Gocht and Kuldeep S. Meel.
In Proceedings of International Conference on Computer-Aided Verification (CAV), July 2020.
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Approximate Counting of Minimal Unsatisfiable Subsets.
Jaroslav Bendik, and Kuldeep S. Meel.
In Proceedings of International Conference on Computer-Aided Verification (CAV), July 2020.
Invited to FMSD issue dedicated to the best papers from CAV 2020
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A Study of Symmetry Breaking Predicates and Model Counting.
Wenxi Wang, Muhammad Usman, Alyas Almaawi, Kaiyuan Wang, Kuldeep S. Meel and Sarfraz Khurshid.
In Proceedings of Tools and Algorithms for the Construction and Analysis of Systems (TACAS), April 2020.
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Principled network reliability approximation: A counting-based approach.
Roger Paredes, Leonardo Duenas-Osorio, Kuldeep S. Meel and Moshe Y. Vardi.
Journal of Reliability Engineering and System Safety(RESS), November 2019.
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Dual Hashing-based Algorithms for Discrete Integration.
de Colnet,Alexis, and Kuldeep S. Meel.
In Proceedings of International Conference on Constraint Programming (CP), October 2019.
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Not All FPRASs are Equal: Demystifying FPRASs for DNF-Counting (Extended Abstract) .
Kuldeep S. Meel, Aditya A. Shrotri and Moshe Y. Vardi.
In Proceedings of International Joint Conference on Artificial Intelligence (IJCAI), August 2019.
Sister Conference Best Papers Track
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Ganak: A Scalable Probabilistic Exact Model Counter.
Shubham Sharma, Subhajit Roy, Mate Soos and Kuldeep S. Meel.
In Proceedings of International Joint Conference on Artificial Intelligence (IJCAI), August 2019.
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Not All FPRASs are Equal: Demystifying FPRASs for DNF-Counting
Kuldeep S. Meel, Aditya A. Shrotri and Moshe Y. Vardi.
Constraints, August 2019.
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BIRD: Engineering an Efficient CNF-XOR SAT Solver and its Applications to Approximate Model Counting .
Mate Soos, and Kuldeep S. Meel.
In Proceedings of AAAI Conference on Artificial Intelligence (AAAI), January 2019.
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On the Hardness of Probabilistic Inference Relaxations.
Supratik Chakraborty, Kuldeep S. Meel and Moshe Y. Vardi.
In Proceedings of AAAI Conference on Artificial Intelligence (AAAI), January 2019.
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Constrained counting and sampling: bridging the gap between theory and practice .
Kuldeep S. Meel.
Ph.D. Thesis, Rice University, 2018.
Winner of 2018 Ralph Budd Award for Best Engineering Thesis and Honorable mention, 2018 ACP Doctoral Dissertation Award
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Not All FPRASs are Equal: Demystifying FPRASs for DNF-Counting.
Kuldeep S. Meel, Aditya A. Shrotri and Moshe Y. Vardi.
In Proceedings of International Conference on Constraint Programming (CP), August 2018.
Sister Conferences Best Paper Track at IJCAI-19
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On Hashing-Based Approaches to Approximate DNF-Counting.
Kuldeep S. Meel, Aditya A. Shrotri and Moshe Y. Vardi.
In Proceedings of IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science (FSTTCS), December 2017.
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Counting-Based Reliability Estimation for Power-Transmission Grids.
Leonardo Duenas-Osorio, Kuldeep S. Meel, Roger Paredes and Moshe Y. Vardi.
In Proceedings of AAAI Conference on Artificial Intelligence (AAAI), February 2017.
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On Computing Minimal Independent Support and Its Applications to Sampling and Counting
Alexander Ivrii, Sharad Malik, Kuldeep S. Meel and Moshe Y. Vardi.
Constraints, 21(1), September 2016.
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Algorithmic Improvements in Approximate Counting for Probabilistic Inference: From Linear to Logarithmic SAT Calls .
Supratik Chakraborty, Kuldeep S. Meel and Moshe Y. Vardi.
In Proceedings of International Joint Conference on Artificial Intelligence (IJCAI), July 2016.
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Approximate Probabilistic Inference via Word-Level Counting.
Supratik Chakraborty, Kuldeep S. Meel, Rakesh Mistry and Moshe Y. Vardi.
In Proceedings of AAAI Conference on Artificial Intelligence (AAAI), June 2016.
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Constrained Sampling and Counting: Universal Hashing meets SAT Solving .
Kuldeep S. Meel, Moshe Y. Vardi, Supratik Chakraborty, Daniel J. Fremont, Sanjit A. Seshia, Dror Fried, Alexander Ivrii and Sharad Malik.
In Proceedings of Workshop on Beyond NP(BNP), February 2016.
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On Computing Minimal Independent Support and Its Applications to Sampling and Counting .
Alexander Ivrii, Sharad Malik, Kuldeep S. Meel and Moshe Y. Vardi.
In Proceedings of International Conference on Constraint Programming (CP), September 2015.
Best Student Paper Award
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From Weighted to Unweighted Model Counting.
Supratik Chakraborty, Dror Fried, Kuldeep S. Meel and Moshe Y. Vardi.
In Proceedings of International Joint Conference on Artificial Intelligence (IJCAI), July 2015.
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Distribution-Aware Sampling and Weighted Model Counting for SAT.
Supratik Chakraborty, Daniel J. Fremont, Kuldeep S. Meel, Sanjit A. Seshia and Moshe Y. Vardi.
In Proceedings of AAAI Conference on Artificial Intelligence (AAAI), July 2014.
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Sampling techniques for boolean satisfiability.
Kuldeep S. Meel.
Master's Thesis, Rice University,2014.
Winner of 2014 VCLA (Vienna Center of Logic and Algorithms) Outstanding Masters Thesis
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A Scalable Approximate Model Counter.
Supratik Chakraborty, Kuldeep S. Meel and Moshe Y. Vardi.
In Proceedings of International Conference on Constraint Programming (CP), pp. 200–216, September 2013.
Selected for CP 25th Anniversary Volume
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Sampling

Scalable Probabilistic Routes.
Suwei Yang, Victor Liang and Kuldeep S. Meel.
In Proceedings of International Conference on Logic for Programming Artificial Intelligence and Reasoning (LPAR), June 2023.
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A scalable tester for samplers.
Yash Pote ⓡ Kuldeep S. Meel.
In Proceedings of Advances in Neural Information Processing Systems(NeurIPS), November 2022.
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INC: A Scalable Incremental Weighted Sampler.
Suwei Yang, and Kuldeep S. Meel.
In Proceedings of Formal Methods in Computer-Aided Design (FMCAD), October 2022.
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On Quantitative Testing of Uniform Samplers.
Mate Soos, Priyanka Golia, Sourav Chakraborty and Kuldeep S. Meel.
In Proceedings of International Conference on Constraint Programming (CP), August 2022.
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On Almost-Uniform Generation of SAT Solutions: The power of 3-wise independent hashing .
Remi Delannoy, and Kuldeep S. Meel.
In Proceedings of Logic in Computer science (LICS), August 2022.
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A Scalable t-wise Coverage Estimator.
Eduard Baranov, Sourav Chakraborty, Axel Legay, Kuldeep S. Meel and N.V. Vinodchandran.
In Proceedings of International Conference on Software Engineering (ICSE), May 2022.
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Designing Samplers is Easy: The Boon of Testers.
Priyanka Golia, Mate Soos, Sourav Chakraborty and Kuldeep S. Meel.
In Proceedings of Formal Methods in Computer-Aided Design (FMCAD), October 2021.
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WAPS: Weighted and Projected Sampling.
Rahul Gupta, Shubham Sharma, Subhajit Roy and Kuldeep S. Meel.
In Proceedings of Tools and Algorithms for the Construction and Analysis of Systems (TACAS), April 2019.
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On testing of Uniform Samplers.
Sourav Chakraborty, and Kuldeep S. Meel.
In Proceedings of AAAI Conference on Artificial Intelligence (AAAI), January 2019.
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Knowledge Compilation meets Uniform Sampling.
Shubham Sharma, Rahul Gupta, Subhajit Roy and Kuldeep S. Meel.
In Proceedings of International Conference on Logic for Programming Artificial Intelligence and Reasoning (LPAR), November 2018.
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On Parallel Scalable Uniform SAT Witness Generator.
Supratik Chakraborty, Daniel J. Fremont, Kuldeep S. Meel, Sanjit A. Seshia and Moshe Y. Vardi.
In Proceedings of Tools and Algorithms for the Construction and Analysis of Systems (TACAS), pp. 304–319, April 2015.
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Balancing Scalability and Uniformity in SAT-Witness Generator.
Supratik Chakraborty, Kuldeep S. Meel and Moshe Y. Vardi.
In Proceedings of Design Automation Conference (DAC), pp. 60:1–60:6, June 2014.
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A Scalable and Nearly Uniform Generator of SAT Witnesses.
Supratik Chakraborty, Kuldeep S. Meel and Moshe Y. Vardi.
In Proceedings of International Conference on Computer-Aided Verification (CAV), pp. 608–622, July 2013.
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Synthesis

The Limitations and Power of NP-Oracle Based Functional Synthesis Techniques .
Brendan Juba, and Kuldeep S. Meel.
In Proceedings of AAAI Conference on Artificial Intelligence (AAAI), pp. 14261–14268, 2026.
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Synthesis with Explicit Dependencies.
Priyanka Golia, Subhajit Roy and Kuldeep S. Meel.
In Proceedings of Design, Automation, and Test in Europe(DATE), April 2023.
Best Paper Award Nomination
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Engineering an Efficient Boolean Functional Synthesis Engine.
Priyanka Golia, Friedrich Slivovsky, Subhajit Roy and Kuldeep S. Meel.
In Proceedings of IEEE/ACM International Conference on Computer-Aided Design (ICCAD), November 2021.
Best Paper Award Nomination
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Program Synthesis as Dependency Quantified Formula Modulo Theory.
Priyanka Golia, Subhajit Roy and Kuldeep S. Meel.
In Proceedings of International Joint Conference on Artificial Intelligence (IJCAI), August 2021.
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Manthan: A Data-Driven Approach for Boolean Function Synthesis.
Priyanka Golia, Subhajit Roy and Kuldeep S. Meel.
In Proceedings of International Conference on Computer-Aided Verification (CAV), July 2020.
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Data Streams

Improved Streaming Algorithm for the Klee's Measure Problem and Generalizations .
Mridul Nandi ⓡ N. V. Vinodchandran ⓡ Arijit Ghosh ⓡ Kuldeep S. Meel ⓡ Soumit Pal ⓡ Chakraborty,Sourav .
In Proceedings of the International Conference on Approximation Algorithms for Combinatorial Optimization Problems (APPROX), August 2024.
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On the Feasibility of Forgetting in Data Streams.
A. Pavan, Sourav, Chakraborty, N. V. Vinodchandran and Kuldeep S. Meel.
In Proceedings of ACM Symposium on Principles of Database Systems (PODS), June 2024.
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Conjunctive Queries on Probabilistic Graphs: The Limits of Approximability .
Antoine Amarilli, Timothy van Bremen and Kuldeep S. Meel.
In Proceedings of the International Conference on Database Theory (ICDT), March 2024.
Selected as one of the 7 best papers from the conference to be invited for a special issue of the journal Logical Methods in Computer Science.
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Distinct Elements in Streams: An Algorithm for the (Text) Book.
Sourav Chakraborty ⓡ N. V. Vinodchandran ⓡ Kuldeep S. Meel.
In Proceedings of European Symposium of Algorithms (ESA), August 2022.
Highlighted in Donald Knuth's note on the paper
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Estimation of the Size of Union of Delphic Sets: Achieving Independence from Stream Size .
Kuldeep S. Meel ⓡ Sourav Chakraborty ⓡ N.V. Vinodchandran.
In Proceedings of ACM Symposium on Principles of Database Systems (PODS), June 2022.
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Estimating the Size of Unions of Sets in Streaming Models.
Kuldeep S. Meel ⓡ N.V. Vinodchandran ⓡ Sourav Chakraborty.
In Proceedings of ACM Symposium on Principles of Database Systems (PODS), June 2021.
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Formal Methods 4 ML

Probabilistic Explanations for Linear Models.
Bernardo Subercaseaux, Marcelo Arenas and Kuldeep S. Meel.
In Proceedings of AAAI Conference on Artificial Intelligence (AAAI), February 2025.
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Solution-Aware Vs Global ReLU Selection: Partial MILP Strikes Back for DNN Verification .
Yuke Liao, Blaise Genest, Kuldeep S. Meel and Shaan Aryaman.
In Proceedings of International Symposium on Automated Technology for Verification and Analysis (ATVA), pp. 299–320, 2025.
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Efficient Certified Reasoning for Binarized Neural Networks.
Jiong Yang, Yong Kiam Tan, Mate Soos, Magnus O. Myreen and Kuldeep S. Meel.
In Proceedings of the International Conference on Theory and Applications of Satisfiability Testing (SAT), pp. 32:1–32:22, 2025.
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Locally-Minimal Probabilistic Explanations.
Yacine Izza, Kuldeep S. Meel and Joao Marques-Silva.
In Proceedings of European Conference on Artificial Intelligence(ECAI), October 2024.
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"How Biased are Your Features?": Computing Fairness Influence Functions with Global Sensitivity Analysis .
Bishwamittra Ghosh, Debabrota Basu and Kuldeep S. Meel.
In Proceedings of the ACM Conference on Fairness, Accountability, and Transparency (FAccT), June 2023.
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Efficient Learning of Interpretable Classification Rules
Bishwamittra Ghosh, Dmitry Malioutov and Kuldeep S. Meel.
Journal of Artificial Intelligence Research (JAIR), 74:1823–1863, September 2022.
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Algorithmic Fairness Verification with Graphical Models.
Bishwamittra Ghosh, Debabrota Basu and Kuldeep S. Meel.
In Proceedings of AAAI Conference on Artificial Intelligence (AAAI), February 2022.
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Constraint-Driven Explanations of Black-Box ML Models.
Aditya Shrotri, Nina Narodytska, Alexey Ignatiev, Kuldeep S. Meel, Joao Marques-Silva and Vardi,Moshe Y. .
In Proceedings of AAAI Conference on Artificial Intelligence (AAAI), February 2022.
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Scalable Quantitative Verification For Deep Neural Networks.
Teodora Baluta, Zheng Leong Chua, Kuldeep S. Meel and Prateek Saxena.
In Proceedings of International Conference on Software Engineering (ICSE), May 2021.
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Justicia: A Stochastic SAT Approach to Formally Verify Fairness.
Bishwamittra Ghosh, Debabrota Basu and Kuldeep S. Meel.
In Proceedings of AAAI Conference on Artificial Intelligence (AAAI), February 2021.
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Classification Rules in Relaxed Logical Form.
Bishwamittra Ghosh, Dmitry Malioutov and Kuldeep S. Meel.
In Proceedings of European Conference on Artificial Intelligence(ECAI), June 2020.
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A MaxSAT-based Framework for Group Testing.
Lorenzo Ciampiconi, Bishwamittra Ghosh, Jonathan Scarlett and Kuldeep S. Meel.
In Proceedings of AAAI Conference on Artificial Intelligence (AAAI), February 2020.
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Embedding Symbolic Knowledge into Deep Networks.
Yaqi Xie, Ziwei Xu, Kankanhalli,Mohan S., Meel,Kuldeep S. and Harold Soh.
In Proceedings of Advances in Neural Information Processing Systems(NeurIPS), December 2019.
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Quantitative Verification of Neural Networks And its Security Applications .
Teodora Baluta, Shiqi Shen, Shine,Shweta, Kuldeep S. Meel and Prateek Saxena.
In Proceedings of ACM Conference on Computer and Communications Security (CCS), November 2019.
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Assessing Heuristic Machine Learning Explanations with Model Counting.
Nina Narodytska, Aditya Shrotri, Kuldeep S. Meel, Alexey Ignatiev and Joao Marques Silva.
In Proceedings of the International Conference on Theory and Applications of Satisfiability Testing (SAT), July 2019.
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IMLI: An Incremental Framework for MaxSAT-Based Learning of Interpretable Classification Rules .
Bishwamittra Ghosh, and Kuldeep S. Meel.
In Proceedings of AAAI/ACM Conference on AI, Ethics, and Society(AIES), January 2019.
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MLIC: A MaxSAT-Based framework for learning interpretable classification rules .
Malioutov,Dmitry, and Kuldeep S. Meel.
In Proceedings of International Conference on Constraint Programming (CP), August 2018.
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Formal Methods

Verification of the CVM Algorithm with a Functional Probabilistic Invariant .
Emin Karayel, Seng Joe Watt, Derek Khu, Kuldeep S. Meel and Yong Kiam Tan.
In Interactive Theorem Proving (ITP), pp. 34:1–34:20, 2025.
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Solver Engineering

Engineering an Efficient Preprocessor for Model Counting.
Mate Soos, and Kuldeep S. Meel.
In Proceedings of Design Automation Conference (DAC), June 2024.
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Explaining SAT Solving Using Causal Reasoning.
Jiong Yang, Arijit Shaw, Teodora Baluta, Mate Soos and Kuldeep S. Meel.
In Proceedings of the International Conference on Theory and Applications of Satisfiability Testing (SAT), July 2023.
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Gaussian Elimination meets Maximum Satisfiability.
Mate Soos, and Kuldeep S. Meel.
In Proceedings of International Conference on Knowledge Representation and Reasoning (KR), November 2021.
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Engineering an Efficient PB-XOR Solver.
Jiong Yang, and Kuldeep S. Meel.
In Proceedings of International Conference on Constraint Programming (CP), September 2021.
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Leveraging GPUs for Effective Clause Sharing in Parallel SAT Solving.
Nicolas Prevot, Mate Soos and Kuldeep S. Meel.
In Proceedings of the International Conference on Theory and Applications of Satisfiability Testing (SAT), July 2021.
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Designing New Phase Selection Heuristics.
Arijit Shaw, and Kuldeep S. Meel.
In Proceedings of the International Conference on Theory and Applications of Satisfiability Testing (SAT), July 2020.
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CrystalBall: Gazing in the Black Box of SAT Solving.
Mate Soos, Raghav Kulkarni and Kuldeep S. Meel.
In Proceedings of the International Conference on Theory and Applications of Satisfiability Testing (SAT), July 2019.
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Bosphorus: Bridging ANF and CNF Solvers.
Davin Choo, Mate Soos, Kian Ming A. Chai and Kuldeep S. Meel.
In Proceedings of Design, Automation, and Test in Europe(DATE), March 2019.
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Distribution Testing

Distance Estimation for High-Dimensional Discrete Distributions.
Kuldeep S. Meel, Gunjan Kumar and Yash Pote.
In Proceedings of International Conference on Artificial Intelligence and Statistics (AISTATS), pp. 955–963, May 2025.
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A scalable entropy estimator
Priyanka Golia, Brendan Juba and Kuldeep S. Meel.
Formal Methods in System Design, 66(2):170–194, 2025.
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Total variation distance for product distributions is #P-complete
Arnab Bhattacharyya, Sutanu Gayen, Kuldeep S. Meel, Dimitrios Myrisiotis, A. Pavan and N. V. Vinodchandran.
Information Processing Letters, 189:106560, 2025.
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Assessing the Quality of Binomial Samplers: A Statistical Distance Framework .
Uddalok Sarkar, Sourav Chakraborty and Kuldeep S. Meel.
In Proceedings of International Conference on Computer-Aided Verification (CAV), pp. 231–253, 2025.
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Computational Explorations of Total Variation Distance.
Arnab Bhattacharyya, Sutanu Gayen, Kuldeep S. Meel, Dimitrios Myrisiotis, A. Pavan and N. V. Vinodchandran.
In Proceedings of the International Conference on Learning Representations (ICLR), 2025.
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Total Variation Distance Meets Probabilistic Inference.
Arnab Bhattacharyya, Sutanu Gayen, Kuldeep S. Meel, Dimitrios Myrisiotis, A. Pavan and N. V. Vinodchandran.
In Proceedings of the International Conference on Machine Learning (ICML), July 2024.
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Equivalence Testing: The Power of Bounded Adaptivity.
Diptarka Chakraborty, Sourav Chakraborty, Gunjan Kumar and Kuldeep S. Meel.
In Proceedings of International Conference on Artificial Intelligence and Statistics (AISTATS), April 2024.
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On Approximating Total Variation Distance.
Arnab Bhattacharyya, Sutanu Gayen, Kuldeep S Meel, Dimitrios Myrisiotis, Pavan A. and N. V. Vinodchandran.
In Proceedings of International Joint Conference on Artificial Intelligence (IJCAI), July 2023.
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On Testing of Horn Samplers.
Ansuman Banerjee, Shayak, Chakraborty, Sourav Chakraborty, Kuldeep S. Meel, Uddalok Sarkar and Sayantan Sen.
In Proceedings of International Conference on Artificial Intelligence and Statistics (AISTATS), April 2023.
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A scalable tester for samplers.
Yash Pote ⓡ Kuldeep S. Meel.
In Proceedings of Advances in Neural Information Processing Systems(NeurIPS), November 2022.
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A Scalable Shannon Entropy Estimator.
Priyanka Golia, Brendan Juba and Kuldeep S. Meel.
In Proceedings of International Conference on Computer-Aided Verification (CAV), August 2022.
Invited to FMSD Special Issue dedicated to the Best Papers from CAV-22
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Testing Probabilistic Circuits.
Yash Pote, and Kuldeep S. Meel.
In Proceedings of Advances in Neural Information Processing Systems(NeurIPS), December 2021.
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Efficient Distance Approximation for Structured High-Dimensional Distributions via Learning .
Arnab Bhattacharyya, Gayen,Sutanu, Kuldeep S. Meel and N. V. Vinodchandran.
In Proceedings of Advances in Neural Information Processing Systems(NeurIPS), December 2020.
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On Testing of Samplers.
Kuldeep S. Meel ⓡ Yash Pote ⓡ Sourav Chakraborty.
In Proceedings of Advances in Neural Information Processing Systems(NeurIPS), December 2020.
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On testing of Uniform Samplers.
Sourav Chakraborty, and Kuldeep S. Meel.
In Proceedings of AAAI Conference on Artificial Intelligence (AAAI), January 2019.
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Knowledge Compilation

Phase Transitions

Phase Transition Behavior in Knowledge Compilation.
Rahul Gupta, Subhajit Roy and Kuldeep S. Meel.
In Proceedings of International Conference on Constraint Programming (CP), September 2020.
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Phase Transition Behavior of Cardinality and XOR Constraints.
Yash Pote, Saurabh Joshi and Kuldeep S. Meel.
In Proceedings of International Joint Conference on Artificial Intelligence (IJCAI), August 2019.
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The Hard Problems Are Almost Everywhere For Random CNF-XOR Formulas.
Jeffrey Dudek, Kuldeep S. Meel and Moshe Y. Vardi.
In Proceedings of International Joint Conference on Artificial Intelligence (IJCAI), August 2017.
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Combining the k-CNF and XOR Phase-Transitions.
Jeffrey Dudek, Kuldeep S. Meel and Moshe Y. Vardi.
In Proceedings of International Joint Conference on Artificial Intelligence (IJCAI), July 2016.
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Software Engineering

Baital: An Adaptive Weighted Sampling Approach for Improved t-wise Coverage .
Eduard Baranov, Axel Legay and Kuldeep S. Meel.
In Proceedings of ACM Joint European Software Engineering Conference and Symposium on the Founda-tions of Software Engineering (ESEC/FSE), November 2020.
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Scalable Approximation of Quantitative Information Flow in Programs.
Fabrizio Biondi, Michael Enescu, Annelie Heuser, Axel Legay, Kuldeep S. Meel and Jean Quilbeuf.
In Proceedings of International Conference on Verification, Model Checking, and Abstract Interpretation (VMCAI), January 2018.
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Automatic Data Layout Generation and Kernel Mapping for CPU+GPU Architectures .
Deepak Majeti, Kuldeep S. Meel, Raj Barik and Vivek Sarkar.
In Proceedings of International Conference on Compiler Construction (CC), March 2016.
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Design and Verification of Distributed Phasers.
Karthik, Murthy, Sri Raj, Paul, Kuldeep S., Meel, Tiago Cogumbreiro and John Mellor-Crummey.
In Proceedings of International European Conference on Parallel and Distributed Computing (Euro-Par), January 2016.
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ADHA: Automatic Data layout framework for Heterogeneous Architectures.
Deepak Majeti, Kuldeep S. Meel, Raj Barik and Vivek Sarkar.
In Proceedings of Parallel Architecture and Compilation Techniques (PACT), August 2014.
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Misc

Solving the Identifying Code Set Problem with Grouped Independent Support .
Anna Latour, Arunabha Sen and Kuldeep S. Meel.
In Proceedings of International Joint Conference on Artificial Intelligence (IJCAI), July 2023.
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Constraint Optimization over Semirings.
A. Pavan ⓡ Kuldeep S. Meel ⓡ N. V. Vinodchandran ⓡ Arnab Bhattacharyya.
In Proceedings of AAAI Conference on Artificial Intelligence (AAAI), January 2023.
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Predicting Forest Fire Using Remote Sensing Data And Machine Learning.
Suwei Yang, Lupascu,Massimo and Kuldeep S. Meel.
In Proceedings of AAAI Conference on Artificial Intelligence (AAAI), February 2021.
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Induction Models on N.
A. Dileep, Kuldeep S. Meel and Ammar F. Sabili.
In Proceedings of International Conference on Logic for Programming Artificial Intelligence and Reasoning (LPAR), April 2020.
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