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 "independence of causal influence and clique tree propagation"):
  Abstract: This paper explores the role of independence of causal influence (ICI) in Bayesian network inference. ICI allows one to factorize a conditional probability table into smaller pieces. We describe a method for exploiting the factorization in clique tree propagation (CTP) - the state-of-the-art exact inference algorithm for Bayesian networks. We also present empirical results showing that the resulting algorithm is significantly more efficient than the combination of CTP and previous techniques for exploiting ICI.

Includes members:
  Member "search based methods to bound diagnostic probabilities in very large belief nets":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "real time top k predictive query processing over event streams")
  Member "utility based abstraction and categorization":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "state space abstraction for anytime evaluation of probabilistic networks")
  Member "approximations in bayesian belief universe for knowledge based systems":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "a tutorial on learning with bayesian networks")
  Member "causal independence for knowledge acquisition and inference":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "exploiting causality for selective belief filtering in dynamic bayesian networks")
  Member "the use of conflicts in searching bayesian networks":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "sample and accumulate algorithms for belief updating in bayes networks")
  Member "a new look at causal independence":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "uno uncertainty aware noisy or multimodal fusion for unanticipated input degradation")
  Member "a generalization of the noisy or model":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "exploiting causality for selective belief filtering in dynamic bayesian networks")
  Member "abstraction in belief networks the role of intermediate states in diagnostic reasoning":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "network engineering for complex belief networks")

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)