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 "tractability through exchangeability a new perspective on efficient probabilistic inference"):
  Abstract: Exchangeability is a central notion in statistics and probability theory. The assumption that an infinite sequence of data points is exchangeable is at the core of Bayesian statistics. However, finite exchangeability as a statistical property that renders probabilistic inference tractable is less well-understood. We develop a theory of finite exchangeability and its relation to tractable probabilistic inference. The theory is complementary to that of independence and conditional independence. We show that tractable inference in probabilistic models with high treewidth and millions of variables can be understood using the notion of finite (partial) exchangeability. We also show that existing lifted inference algorithms implicitly utilize a combination of conditional independence and partial exchangeability.

Includes members:
  Member "exchangeable variable models":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "lifted filtering via exchangeable decomposition")
  Member "on the complexity and approximation of binary evidence in lifted inference":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "taming reasoning in temporal probabilistic relational models")
  Member "context specific independence in bayesian networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "abstracting probabilistic models a logical perspective")
  Member "symmetry aware marginal density estimation":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "generating and sampling orbits for lifted probabilistic inference")
  Member "rockit exploiting parallelism and symmetry for map inference in statistical relational models":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "beyond markov logic efficient mining of prediction rules in large graphs")
  Member "automorphism groups of graphical models and lifted variational inference":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "generating and sampling orbits for lifted probabilistic inference")
  Member "markov chains on orbits of permutation groups":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "generating and sampling orbits for lifted probabilistic inference")
  Member "probabilistic theorem proving":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "equivalence of dataflow graphs via rewrite rules using a graph to sequence neural model")

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)