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 "structured arc reversal and simulation of dynamic probabilistic networks"):
  Abstract: We present an algorithm for arc reversal in Bayesian networks with tree-structured conditional probability tables, and consider some of its advantages, especially for the simulation of dynamic probabilistic networks. In particular, the method allows one to produce CPTs for nodes involved in the reversal that exploit regularities in the conditional distributions. We argue that this approach alleviates some of the overhead associated with arc reversal, plays an important role in evidence integration and can be used to restrict sampling of variables in DPNs. We also provide an algorithm that detects the dynamic irrelevance of state variables in forward simulation. This algorithm exploits the structured CPTs in a reversed network to determine, in a time-independent fashion, the conditions under which a variable does or does not need to be sampled.

Includes members:
  Member "sensor validation using dynamic belief networks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "bayes networks for sonar sensor fusion")
  Member "a computational scheme for reasoning in dynamic probabilistic networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "learning the structure of dynamic probabilistic networks")
  Member "learning bayesian networks with local structure":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "a meta transfer objective for learning to disentangle causal mechanisms")
  Member "advances in probabilistic reasoning":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "multi context models for reasoning under partial knowledge generative process and inference grammar")
  Member "a graph theoretic analysis of information value":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "active learning amidst logical knowledge")
  Member "context specific independence in bayesian networks":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "abstracting probabilistic models a logical perspective")
  Member "weighing and integrating evidence for stochastic simulation in bayesian networks":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "gaussian mixture reduction for time constrained approximate inference in hybrid bayesian 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)