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 "spatial coupling as a proof technique"):
  Abstract: The aim of this paper is to show that spatial coupling can be viewed not only as a means to build better graphical models, but also as a tool to better understand uncoupled models. The starting point is the observation that some asymptotic properties of graphical models are easier to prove in the case of spatial coupling. In such cases, one can then use the so-called interpolation method to transfer results known for the spatially coupled case to the uncoupled one. Our main application of this framework is to LDPC codes, where we use interpolation to show that the average entropy of the codeword conditioned on the observation is asymptotically the same for spatially coupled as for uncoupled ensembles. We use this fact to prove the so-called Maxwell conjecture for a large class of ensembles. In a first paper last year, we have successfully implemented this strategy for the case of LDPC ensembles where the variable node degree distribution is Poisson. In the current paper we now show how to treat the practically more relevant case of general variable degree distributions. In particular, regular ensembles fall within this framework. As we will see, a number of technical difficulties appear when compared to the simpler case of Pois son- distributed degrees. For our arguments to hold we need symmetry to be present. For coding, this symmetry follows from the channel symmetry; for general graphical models the required symmetry is called Nishimori symmetry.

Includes members:
  Member "threshold saturation for spatially coupled ldpc and ldgm codes on bms channels":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "capacity achieving spatially coupled sparse superposition codes with amp decoding")
  Member "threshold saturation in spatially coupled constraint satisfaction problems":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "universal sparse superposition codes with spatial coupling and gamp decoding")
  Member "spatially coupled ensembles universally achieve capacity under belief propagation":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "capacity achieving spatially coupled sparse superposition codes with amp decoding")
  Member "sharp bounds for optimal decoding of low density parity check codes":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "overlap matrix concentration in optimal bayesian inference")
  Member "maxwell construction the hidden bridge between iterative and maximum a posteriori decoding":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "reed muller codes theory and algorithms")
  Member "the generalized area theorem and some of its consequences":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "reed muller codes theory and algorithms")
  Member "tight bounds for ldpc and ldgm codes under map decoding":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "accuracy memory tradeoffs and phase transitions in belief propagation")

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)