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 "mutual information in community detection with covariate information and correlated networks"):
  Abstract: We study the problem of community detection when there is covariate information about the node labels and one observes multiple correlated networks. We provide an asymptotic upper bound on the per-node mutual information as well as a heuristic analysis of a multivariate performance measure called the MMSE matrix. These results show that the combined effects of seemingly very different types of information can be characterized explicitly in terms of formulas involving low-dimensional estimation problems in additive Gaussian noise. Our analysis is supported by numerical simulations.

Includes members:
  Member "the geometry of community detection via the mmse matrix":
    also connected through other hyperedges:
      (none)
  Member "community detection with side information exact recovery under the stochastic block model":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "exit analysis for community detection")
  Member "information theoretic thresholds from the cavity method":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "optimal errors and phase transitions in high dimensional generalized linear models")
  Member "the computer science and physics of community detection landscapes phase transitions and hardness":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "mean field theory of graph neural networks in graph partitioning")
  Member "structure and inference in annotated networks":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "on a scalable entropic breaching of the overfitting barrier in machine learning")
  Member "mutual information in rank one matrix estimation":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "overlap matrix concentration in optimal bayesian inference")
  Member "mutual information for symmetric rank one matrix estimation a proof of the replica formula":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "capacity achieving spatially coupled sparse superposition codes with amp decoding")
  Member "phase transitions in semisupervised clustering of sparse networks":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "renyi entropy bounds on the active learning cost performance tradeoff")

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.IT(Information Theory)