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 "multivariate spatiotemporal hawkes processes and network reconstruction"):
  Abstract: There is often latent network structure in spatial and temporal data and the tools of network analysis can yield fascinating insights into such data. In this paper, we develop a nonparametric method for network reconstruction from spatiotemporal data sets using multivariate Hawkes processes. In contrast to prior work on network reconstruction with point-process models, which has often focused on exclusively temporal information, our approach uses both temporal and spatial information and does not assume a specific parametric form of network dynamics. This leads to an effective way of recovering an underlying network. We illustrate our approach using both synthetic networks and networks constructed from real-world data sets (a location-based social media network, a narrative of crime events, and violent gang crimes). Our results demonstrate that, in comparison to using only temporal data, our spatiotemporal approach yields improved network reconstruction, providing a basis for meaningful subsequent analysis --- such as community structure and motif analysis --- of the reconstructed networks.

Includes members:
  Member "inferring multiplex diffusion network via multivariate marked hawkes process":
    also connected through other hyperedges:
      (none)
  Member "graph based deep modeling and real time forecasting of sparse spatio temporal data":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "riskoracle a minute level citywide traffic accident forecasting framework")
  Member "the role of network analysis in industrial and applied mathematics a physical applied mathematics perspective":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "nonlinearity networks a 2020 vision")
  Member "crime topic modeling":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "prediction focused topic models via feature selection")
  Member "latent self exciting point process model for spatial temporal networks":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "diffusion on dynamic contact networks with indirect transmission links")
  Member "the geospatial characteristics of a social movement communication network":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "bots elections and social media a brief overview")
  Member "modeling events with cascades of poisson processes":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "a multi channel neural graphical event model with negative evidence")
  Member "the anatomy of the facebook social graph":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "graph bert only attention is needed for learning graph representations")

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)