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: "exact topology reconstruction of radial dynamical systems with applications to distribution system of the power grid"
  Abstract: In this article we present a method to reconstruct the interconnectedness of dynamically related stochastic processes, where the interactions are bi-directional and the underlying topology is a tree. Our approach is based on multivariate Wiener filtering which recovers spurious edges apart from the true edges in the topology reconstruction. The main contribution of this work is to show that all spurious links obtained using Wiener filtering can be eliminated if the underlying topology is a tree based on which we present a three stage network reconstruction procedure for trees. We illustrate the effectiveness of the method developed by applying it on a typical distribution system of the electric grid.

Connected through hyperedge HE-1 (induced by source paper "graphical models in loopy distribution grids topology estimation change detection and limitation"):
  with members:
    - "topology estimation using graphical models in multi phase power distribution grids"
    - "exact topology and parameter estimation in distribution grids with minimal observability"
    - "data driven approach for distribution network topology detection"
    - "feeder topology identification"

Connected through hyperedge HE-2 (induced by source paper "topology estimation using graphical models in multi phase power distribution grids"):
  with members:
    - "online learning of power transmission dynamics"
    - "data driven approach for distribution network topology detection"
    - "feeder topology identification"
    - "grid topology identification using electricity prices"
    - "kernel based conditional independence test and application in causal discovery"

Connected through hyperedge HE-3 (induced by source paper "joint estimation of topology injection statistics in distribution grids with missing nodes"):
  with members:
    - "topology estimation using graphical models in multi phase power distribution grids"
    - "data driven approach for distribution network topology detection"
    - "feeder topology identification"

Connected through hyperedge HE-4 (induced by source paper "data driven identification of a thermal network in multi zone building"):
  with members:
    - "learning the exact topology of undirected consensus networks"

Connected through hyperedge HE-5 (induced by source paper "learning the exact topology of undirected consensus networks"):
  with members:
    - "optimal topology design for disturbance minimization in power grids"
    - "distributed constrained optimization by consensus based primal dual perturbation method"
    - "topology identification of directed dynamical networks via power spectral analysis"

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.LG(Machine Learning)