human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "coupled graphical models and their thresholds"
  Abstract: The excellent performance of convolutional low-density parity-check codes is the result of the spatial coupling of individual underlying codes across a window of growing size, but much smaller than the length of the individual codes. Remarkably, the belief-propagation threshold of the coupled ensemble is boosted to the maximum-a-posteriori one of the individual system. We investigate the generality of this phenomenon beyond coding theory: we couple general graphical models into a one-dimensional chain of large individual systems. For the later we take the Curie-Weiss, random field Curie-Weiss, $K$-satisfiability, and $Q$-coloring models. We always find, based on analytical as well as numerical calculations, that the message passing thresholds of the coupled systems come very close to the static ones of the individual models. The remarkable properties of convolutional low-density parity-check codes are a manifestation of this very general phenomenon.

Connected through hyperedge HE-1 (induced by source paper "rank one matrix estimation analysis of algorithmic and information theoretic limits by the spatial coupling method"):
  with members:
    - "universal sparse superposition codes with spatial coupling and gamp decoding"
    - "mutual information and optimality of approximate message passing in random linear estimation"
    - "a nearly tight sum of squares lower bound for the planted clique problem"
    - "mutual information in rank one matrix estimation"
    - "asymptotic mutual information for the two groups stochastic block model"
    - "mmse of probabilistic low rank matrix estimation universality with respect to the output channel"
    - "information theoretically optimal sparse pca"
    - "a simple proof of maxwell saturation for coupled scalar recursions"

Connected through hyperedge HE-2 (induced by source paper "universal sparse superposition codes with spatial coupling and gamp decoding"):
  with members:
    - "optimal errors and phase transitions in high dimensional generalized linear models"
    - "plug in estimation in high dimensional linear inverse problems a rigorous analysis"
    - "techniques for improving the finite length performance of sparse superposition codes"
    - "a compressed sensing approach for distribution matching"
    - "approximate message passing decoder and capacity achieving sparse superposition codes"
    - "capacity achieving sparse superposition codes via approximate message passing decoding"
    - "state evolution for approximate message passing with non separable functions"
    - "generalized approximate message passing decoder for universal sparse superposition codes"

Connected through hyperedge HE-3 (induced by source paper "approximate message passing decoder and capacity achieving sparse superposition codes"):
  with members:
    - "capacity achieving sparse superposition codes via approximate message passing decoding"
    - "generalized approximate message passing decoder for universal sparse superposition codes"
    - "the replica symmetric prediction for compressed sensing with gaussian matrices is exact"
    - "threshold saturation of spatially coupled sparse superposition codes for all memoryless channels"
    - "phase transitions and sample complexity in bayes optimal matrix factorization"
    - "the mutual information in random linear estimation"
    - "proof of threshold saturation for spatially coupled sparse superposition codes"
    - "compressive phase retrieval via generalized approximate message passing"

Connected through hyperedge HE-4 (induced by source paper "mutual information and optimality of approximate message passing in random linear estimation"):
  with members:
    - "approximate message passing decoder and capacity achieving sparse superposition codes"
    - "capacity achieving sparse superposition codes via approximate message passing decoding"
    - "the replica symmetric prediction for compressed sensing with gaussian matrices is exact"
    - "threshold saturation of spatially coupled sparse superposition codes for all memoryless channels"
    - "the mutual information in random linear estimation"
    - "proof of threshold saturation for spatially coupled sparse superposition codes"
    - "mutual information in rank one matrix estimation"
    - "mutual information for symmetric rank one matrix estimation a proof of the replica formula"

Connected through hyperedge HE-5 (induced by source paper "the velocity of the propagating wave for spatially coupled systems with applications to ldpc codes"):
  with members:
    - "analysis of coupled scalar systems by displacement convexity"
    - "the velocity of the propagating wave for general coupled scalar systems"
    - "the velocity of the decoding wave for spatially coupled codes on bms channels"
    - "finite length scaling based on belief propagation for spatially coupled ldpc codes"
    - "a scaling law to predict the finite length performance of spatially coupled ldpc codes"
    - "threshold saturation for spatially coupled ldpc and ldgm codes on bms channels"
    - "a simple proof of maxwell saturation for coupled scalar recursions"
    - "approaching the rate distortion limit with spatial coupling belief propagation and decimation"

Connected through hyperedge HE-6 (induced by source paper "i mmse relations in random linear estimation and a sub extensive interpolation method"):
  with members:
    - "mutual information and optimality of approximate message passing in random linear estimation"
    - "the replica symmetric prediction for compressed sensing with gaussian matrices is exact"
    - "the mutual information in random linear estimation"
    - "proof of threshold saturation for spatially coupled sparse superposition codes"
    - "mutual information for symmetric rank one matrix estimation a proof of the replica formula"
    - "threshold saturation for spatially coupled ldpc and ldgm codes on bms channels"
    - "a simple proof of threshold saturation for coupled scalar recursions"
    - "support recovery with sparsely sampled free random matrices"

Connected through hyperedge HE-7 (induced by source paper "the velocity of the propagating wave for general coupled scalar systems"):
  with members:
    - "analysis of coupled scalar systems by displacement convexity"
    - "the velocity of the decoding wave for spatially coupled codes on bms channels"
    - "a simple proof of maxwell saturation for coupled scalar recursions"
    - "threshold saturation in spatially coupled constraint satisfaction problems"
    - "on the convergence speed of spatially coupled ldpc ensembles"
    - "displacement convexity a useful framework for the study of spatially coupled codes"
    - "spatially coupled ensembles universally achieve capacity under belief propagation"
    - "chains of mean field models"

Connected through hyperedge HE-8 (induced by source paper "displacement convexity in spatially coupled scalar recursions"):
  with members:
    - "analysis of coupled scalar systems by displacement convexity"
    - "a simple proof of maxwell saturation for coupled scalar recursions"
    - "threshold saturation in spatially coupled constraint satisfaction problems"
    - "displacement convexity a useful framework for the study of spatially coupled codes"
    - "spatially coupled ensembles universally achieve capacity under belief propagation"
    - "chains of mean field models"
    - "approaching capacity at high rates with iterative hard decision decoding"
    - "wave like solutions of general one dimensional spatially coupled systems"

Question: Please tell me which class the center node 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)