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: "beyond log supermodularity lower bounds and the bethe partition function"
  Abstract: A recent result has demonstrated that the Bethe partition function always lower bounds the true partition function of binary, log-supermodular graphical models. We demonstrate that these results can be extended to other interesting classes of graphical models that are not necessarily binary or log-supermodular: the ferromagnetic Potts model with a uniform external field and its generalizations and special classes of weighted graph homomorphism problems.

Connected through hyperedge HE-1 (induced by source paper "lifted hybrid variational inference"):
  with members:
    - "coarse to fine lifted map inference in computer vision"
    - "lifted tree reweighted variational inference"
    - "belief optimization for binary networks a stable alternative to loopy belief propagation"
    - "lifted relational variational inference"
    - "lifted inference for relational continuous models"
    - "counting belief propagation"
    - "the bethe partition function of log supermodular graphical models"
    - "nonparametric variational inference"

Connected through hyperedge HE-2 (induced by source paper "structure learning using forced pruning"):
  with members:
    - "maximum likelihood bounded tree width markov networks"
    - "efficient stepwise selection in decomposable models"

Connected through hyperedge HE-3 (induced by source paper "counting in graph covers a combinatorial characterization of the bethe entropy function"):
  with members:
    - "the bethe permanent of a nonnegative matrix"
    - "new generalizations of the bethe approximation via asymptotic expansion"
    - "central approximation in statistical physics and information theory"
    - "the bethe partition function of log supermodular graphical models"
    - "pseudocodewords from bethe permanents"
    - "connection between annealed free energy and belief propagation on random factor graph ensembles"
    - "normal factor graphs and holographic transformations"
    - "on the growth rate of the weight distribution of irregular doubly generalized ldpc codes"

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.DM(Discrete Mathematics)