human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "constrained sampling and counting universal hashing meets sat solving"):
  Abstract: Constrained sampling and counting are two fundamental problems in artificial intelligence with a diverse range of applications, spanning probabilistic reasoning and planning to constrained-random verification. While the theory of these problems was thoroughly investigated in the 1980s, prior work either did not scale to industrial size instances or gave up correctness guarantees to achieve scalability. Recently, we proposed a novel approach that combines universal hashing and SAT solving and scales to formulas with hundreds of thousands of variables without giving up correctness guarantees. This paper provides an overview of the key ingredients of the approach and discusses challenges that need to be overcome to handle larger real-world instances.

Includes members:
  Member "distribution aware sampling and weighted model counting for sat":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "on the approximability of weighted model integration on dnf structures")
  Member "balancing scalability and uniformity in sat witness generator":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "quantitative verification of neural networks and its security applications")
  Member "a scalable approximate model counter":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "quantitative verification of neural networks and its security applications")
  Member "taming the curse of dimensionality discrete integration by hashing and optimization":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "towards efficient discrete integration via adaptive quantile queries")
  Member "a scalable and nearly uniform generator of sat witnesses":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "constrained counting and sampling bridging the gap between theory and practice")
  Member "optimization with parity constraints from binary codes to discrete integration":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "quantitative verification of neural networks and its security applications")
  Member "uniform solution sampling using a constraint solver as an oracle":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "exploiting database management systems and treewidth for counting")
  Member "complexity results and approximation strategies for map explanations":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "approximate mmap by marginal search")

Question: Please tell me which class the source paper belongs to. The 40 classes are: cs.NA(Numerical Analysis), cs.MM(Multimedia), cs.LO(Logic in Computer Science), cs.CY(Computers and Society), cs.CR(Cryptography and Security), cs.DC(Distributed, Parallel, and Cluster Computing), cs.HC(Human-Computer Interaction), cs.CE(Computational Engineering, Finance, and Science), cs.NI(Networking and Internet Architecture), cs.CC(Computational Complexity), cs.AI(Artificial Intelligence), cs.MA(Multiagent Systems), cs.GL(General Literature), cs.NE(Neural and Evolutionary Computing), cs.SC(Symbolic Computation), cs.AR(Hardware Architecture), cs.CV(Computer Vision and Pattern Recognition), cs.GR(Graphics), cs.ET(Emerging Technologies), cs.SY(Systems and Control), cs.CG(Computational Geometry), cs.OH(Other Computer Science), cs.PL(Programming Languages), cs.SE(Software Engineering), cs.LG(Machine Learning), cs.SD(Sound), cs.SI(Social and Information Networks), cs.RO(Robotics), cs.IT(Information Theory), cs.PF(Performance), cs.CL(Computation and Language), cs.IR(Information Retrieval), cs.MS(Mathematical Software), cs.FL(Formal Languages and Automata Theory), cs.DS(Data Structures and Algorithms), cs.OS(Operating Systems), cs.GT(Computer Science and Game Theory), cs.DB(Databases), cs.DL(Digital Libraries), cs.DM(Discrete Mathematics). Directly output the class name.

gpt: cs.AI(Artificial Intelligence)