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 "localisation of directional scale discretised wavelets on the sphere"):
  Abstract: Scale-discretised wavelets yield a directional wavelet framework on the sphere where a signal can be probed not only in scale and position but also in orientation. Furthermore, a signal can be synthesised from its wavelet coefficients exactly, in theory and practice (to machine precision). Scale-discretised wavelets are closely related to spherical needlets (both were developed independently at about the same time) but relax the axisymmetric property of needlets so that directional signal content can be probed. Needlets have been shown to satisfy important quasi-exponential localisation and asymptotic uncorrelation properties. We show that these properties also hold for directional scale-discretised wavelets on the sphere and derive similar localisation and uncorrelation bounds in both the scalar and spin settings. Scale-discretised wavelets can thus be considered as directional needlets.

Includes members:
  Member "directional spin wavelets on the sphere":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "sparse image reconstruction on the sphere analysis and synthesis")
  Member "a novel sampling theorem on the rotation group":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "parallelization of the fft on so 3")
  Member "on the computation of directional scale discretized wavelet transforms on the sphere":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "sparse image reconstruction on the sphere analysis and synthesis")
  Member "fourier laguerre transform convolution and wavelets on the ball":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "h cnns convolutional neural networks for riemannian homogeneous spaces")
  Member "s2let a code to perform fast wavelet analysis on the sphere":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "sparse image reconstruction on the sphere analysis and synthesis")
  Member "exact wavelets on the ball":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "sparse image reconstruction on the sphere analysis and synthesis")
  Member "a novel sampling theorem on the sphere":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "variable viewpoint representations for 3d object recognition")

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)