human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "graphon games a statistical framework for network games and interventions"):
  Abstract: In this paper, we introduce a new class of infinite population games, which we term graphon games. As a first contribution, we show that graphon games can be used to describe strategic behavior in heterogeneous populations of infinite size. We establish existence and uniqueness of graphon equilibria and derive general comparative statics results. As a second contribution, we study the equilibria of an ensemble of finite network games sampled from a stochastic network formation process (represented by the graphon). We provide explicit bounds on the distance of the equilibrium of any finite sampled network game and the corresponding graphon equilibrium in terms of the population size, and we characterize optimal interventions in sampled network games by a planner who knows the graphon but not the realization of the sampled network. Finally, as a third contribution, we relax the assumption that agents know the sampled network and establish a tight link between the graphon equilibrium and the Bayesian Nash equilibrium of an incomplete information network game sampled from the same graphon.

Includes members:
  Member "centrality measures for graphons accounting for uncertainty in networks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "graphon pooling in graph neural networks")
  Member "targeting interventions in networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "provable computational and statistical guarantees for efficient learning of continuous action graphical games")
  Member "distributions of centrality on networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "centrality measures for graphons accounting for uncertainty in networks")

Question: Please tell me which class the source paper 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.GT(Computer Science and Game Theory)