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: "sigma point belief propagation"
  Abstract: The sigma point (SP) filter, also known as unscented Kalman filter, is an attractive alternative to the extended Kalman filter and the particle filter. Here, we extend the SP filter to nonsequential Bayesian inference corresponding to loopy factor graphs. We propose sigma point belief propagation (SPBP) as a low-complexity approximation of the belief propagation (BP) message passing scheme. SPBP achieves approximate marginalizations of posterior distributions corresponding to (generally) loopy factor graphs. It is well suited for decentralized inference because of its low communication requirements. For a decentralized, dynamic sensor localization problem, we demonstrate that SPBP can outperform nonparametric (particle-based) BP while requiring significantly less computations and communications.

Connected through hyperedge HE-1 (induced by source paper "peregrine network localization and navigation with scalable inference and efficient operation"):
  with members:
    - "pricing mechanisms for crowd sensed spatial statistics based radio mapping"
    - "csi based fingerprinting for indoor localization a deep learning approach"
    - "data collection and wireless communication in internet of things iot using economic analysis and pricing models a survey"
    - "distributed maximum likelihood sensor network localization"
    - "cramer rao bounds for joint rss doa based primary user localization in cognitive radio networks"
    - "fundamental limits of wideband localization part ii cooperative networks"
    - "fundamental limits of wideband localization part i a general framework"

Connected through hyperedge HE-2 (induced by source paper "partial consensus and conservative fusion of gaussian mixtures for distributed phd fusion"):
  with members:
    - "robust distributed fusion with labeled random finite sets"
    - "distributed smc phd fusion for partial arithmetic average consensus"
    - "a scalable algorithm for tracking an unknown number of targets using multiple sensors"
    - "distributed fusion with multi bernoulli filter based on generalized covariance intersection"
    - "diffusion adaptation over networks"

Connected through hyperedge HE-3 (induced by source paper "cooperative simultaneous localization and synchronization in mobile agent networks"):
  with members:
    - "cooperative joint localization and clock synchronization based on gaussian message passing in asynchronous wireless networks"
    - "space time hierarchical graph based cooperative localization in wireless sensor networks"
    - "cooperative synchronization in wireless networks"
    - "joint localization and clock synchronization for wireless sensor networks"

Connected through hyperedge HE-4 (induced by source paper "toa based passive localization of multiple targets with inaccurate receivers based on belief propagation on factor graph"):
  with members:
    - "simultaneous distributed sensor self localization and target tracking using belief propagation and likelihood consensus"
    - "fundamental limits of wideband localization part i a general framework"

Connected through hyperedge HE-5 (induced by source paper "cooperative localization for mobile networks a distributed belief propagation mean field message passing algorithm"):
  with members:
    - "merging belief propagation and the mean field approximation a free energy approach"

Connected through hyperedge HE-6 (induced by source paper "cooperative simultaneous localization and tracking in mobile agent networks"):
  with members:
    - "approximate evaluation of marginal association probabilities with belief propagation"
    - "cooperative synchronization in wireless networks"
    - "belief consensus algorithms for fast distributed target tracking in wireless sensor networks"
    - "simultaneous distributed sensor self localization and target tracking using belief propagation and likelihood consensus"
    - "gossip algorithms for distributed signal processing"

Connected through hyperedge HE-7 (induced by source paper "distributed localization and tracking of mobile networks including noncooperative objects extended version"):
  with members:
    - "approximate evaluation of marginal association probabilities with belief propagation"
    - "cooperative synchronization in wireless networks"
    - "belief consensus algorithms for fast distributed target tracking in wireless sensor networks"
    - "simultaneous distributed sensor self localization and target tracking using belief propagation and likelihood consensus"
    - "gossip algorithms for distributed signal processing"

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)