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: "approximate inference on planar graphs using loop calculus and belief propagation"
  Abstract: We introduce novel results for approximate inference on planar graphical models using the loop calculus framework. The loop calculus (Chertkov and Chernyak, 2006) allows to express the exact partition function of a graphical model as a finite sum of terms that can be evaluated once the belief propagation (BP) solution is known. In general, full summation over all correction terms is intractable. We develop an algorithm for the approach presented in (Certkov et al., 2008) which represents an efficient truncation scheme on planar graphs and a new representation of the series in terms of Pfaffians of matrices. We analyze the performance of the algorithm for the partition function approximation for models with binary variables and pairwise interactions on grids and other planar graphs. We study in detail both the loop series and the equivalent Pfaffian series and show that the first term of the Pfaffian series for the general, intractable planar model, can provide very accurate approximations. The algorithm outperforms previous truncation schemes of the loop series and is competitive with other state-of-the-art methods for approximate inference.

Connected through hyperedge HE-1 (induced by source paper "gauges loops and polynomials for partition functions of graphical models"):
  with members:
    - "the ising partition function zeros and deterministic approximation"
    - "belief propagation bethe approximation and polynomials"
    - "a generalization of permanent inequalities and applications in counting and optimization"
    - "how to calculate partition functions using convex programming hierarchies provable bounds for variational methods"
    - "a faster approximation algorithm for the gibbs partition function"
    - "the bethe permanent of a nonnegative matrix"
    - "counting in graph covers a combinatorial characterization of the bethe entropy function"
    - "a cluster cumulant expansion at the fixed points of belief propagation"

Connected through hyperedge HE-2 (induced by source paper "discrete geometric analysis of message passing algorithm on graphs"):
  with members:
    - "loopy belief propagation for approximate inference an empirical study"
    - "expectation propagation for approximate bayesian inference"
    - "belief optimization for binary networks a stable alternative to loopy belief propagation"
    - "graph zeta function in the bethe free energy and loopy belief propagation"
    - "gaussian belief propagation solver for systems of linear equations"
    - "belief propagation and beyond for particle tracking"
    - "polynomial linear programming with gaussian belief propagation"
    - "pseudo codewords of cycle codes via zeta functions"

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)