human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "sufficient conditions for convergence of loopy belief propagation"
  Abstract: We derive novel sufficient conditions for convergence of Loopy Belief Propagation (also known as the Sum-Product algorithm) to a unique fixed point. Our results improve upon previously known conditions. For binary variables with (anti-)ferromagnetic interactions, our conditions seem to be sharp.

Connected through hyperedge HE-1 (induced by source paper "efficient attack graph analysis through approximate inference"):
  with members:
    - "exact inference techniques for the analysis of bayesian attack graphs"
    - "loopy belief propagation for approximate inference an empirical study"
    - "belief optimization for binary networks a stable alternative to loopy belief propagation"

Connected through hyperedge HE-2 (induced by source paper "approximating the bethe partition function"):
  with members:
    - "on map inference by mwss on perfect graphs"
    - "loopy belief propagation for approximate inference an empirical study"
    - "belief optimization for binary networks a stable alternative to loopy belief propagation"
    - "bethe bounds and approximating the global optimum"
    - "what cannot be learned with bethe approximations"
    - "on the partition function and random maximum a posteriori perturbations"
    - "convexifying the bethe free energy"
    - "complexity of inference in graphical models"

Connected through hyperedge HE-3 (induced by source paper "generalized belief propagation on tree robust structured region graphs"):
  with members:
    - "loopy belief propagation for approximate inference an empirical study"
    - "belief optimization for binary networks a stable alternative to loopy belief propagation"
    - "on the choice of regions for generalized belief propagation"
    - "convergent message passing algorithms for inference over general graphs with convex free energies"
    - "iterative join graph propagation"
    - "residual belief propagation informed scheduling for asynchronous message passing"
    - "structured region graphs morphing ep into gbp"
    - "convergent message passing algorithms a unifying view"

Connected through hyperedge HE-4 (induced by source paper "convergent message passing algorithms for inference over general graphs with convex free energies"):
  with members:
    - "loopy belief propagation for approximate inference an empirical study"
    - "map estimation linear programming and belief propagation with convex free energies"
    - "convergent propagation algorithms via oriented trees"
    - "a new class of upper bounds on the log partition function"

Connected through hyperedge HE-5 (induced by source paper "residual belief propagation informed scheduling for asynchronous message passing"):
  with members:
    - "expectation propagation for approximate bayesian inference"
    - "belief optimization for binary networks a stable alternative to loopy belief propagation"

Connected through hyperedge HE-6 (induced by source paper "accuracy bounds for belief propagation"):
  with members:
    - "a new class of upper bounds on the log partition function"

Connected through hyperedge HE-7 (induced by source paper "norm product belief propagation primal dual message passing for approximate inference"):
  with members:
    - "convergent message passing algorithms for inference over general graphs with convex free energies"
    - "map estimation linear programming and belief propagation with convex free energies"
    - "convergent message passing algorithms a unifying view"
    - "tightening lp relaxations for map using message passing"
    - "on the optimality of tree reweighted max product message passing"
    - "convexifying the bethe free energy"
    - "convergent propagation algorithms via oriented trees"
    - "a new class of upper bounds on the log partition function"

Connected through hyperedge HE-8 (induced by source paper "sufficient conditions for convergence of the sum product algorithm"):
  with members:
    - "expectation propagation for approximate bayesian inference"
    - "residual belief propagation informed scheduling for asynchronous message passing"
    - "loopy belief propogation and gibbs measures"
    - "survey propagation an algorithm for satisfiability"

Question: Please tell me which class the center node 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)