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 "network interpolation"):
  Abstract: Given a set of snapshots from a temporal network we develop, analyze, and experimentally validate a so-called network interpolation scheme. Our method allows us to build a plausible, albeit random, sequence of graphs that transition between any two given graphs. Importantly, our model is well characterized by a Markov chain, and we leverage this representation to analytically estimate the hitting time (to a predefined distance to the target graph) and long term behavior of our model. These observations also serve to provide interpretation and justification for a rate parameter in our model. Lastly, through a mix of synthetic and real-world data experiments we demonstrate that our model builds reasonable graph trajectories between snapshots, as measured through various graph statistics. In these experiments, we find that our interpolation scheme compares favorably to common network growth models, such as preferential attachment and triadic closure.

Includes members:
  Member "simplicial closure and higher order link prediction":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "hypergraph motifs concepts algorithms and discoveries")
  Member "choosing to grow a graph modeling network formation as discrete choice":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "choice set optimization under discrete choice models of group decisions")
  Member "a sampling framework for counting temporal motifs":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "item independent temporal motifs to summarize and compare temporal networks")
  Member "motifs in temporal networks":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "hypergraph motifs concepts algorithms and discoveries")
  Member "when is a network a network multi order graphical model selection in pathways and temporal networks":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "honem network embedding using higher order patterns in sequential data")
  Member "dynamic stochastic blockmodels for time evolving social networks":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "variational graph recurrent neural 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.SI(Social and Information Networks)