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: "wavelet scattering on the pitch spiral"
  Abstract: We present a new representation of harmonic sounds that linearizes the dynamics of pitch and spectral envelope, while remaining stable to deformations in the time-frequency plane. It is an instance of the scattering transform, a generic operator which cascades wavelet convolutions and modulus nonlinearities. It is derived from the pitch spiral, in that convolutions are successively performed in time, log-frequency, and octave index. We give a closed-form approximation of spiral scattering coefficients for a nonstationary generalization of the harmonic source-filter model.

Connected through hyperedge HE-1 (induced by source paper "one or two components the scattering transform answers"):
  with members:
    - "joint time frequency scattering"
    - "extended playing techniques the next milestone in musical instrument recognition"
    - "look listen and learn"
    - "deep scattering spectrum"

Connected through hyperedge HE-2 (induced by source paper "the shape of remixxxes to come audio texture synthesis with time frequency scattering"):
  with members:
    - "on time frequency scattering and computer music"
    - "neural audio synthesis of musical notes with wavenet autoencoders"
    - "machine listening intelligence"
    - "fader networks manipulating images by sliding attributes"
    - "bitwise neural networks"
    - "joint time frequency scattering for audio classification"
    - "idealized computational models for auditory receptive fields"
    - "deep scattering spectrum"

Connected through hyperedge HE-3 (induced by source paper "learning the helix topology of musical pitch"):
  with members:
    - "extended playing techniques the next milestone in musical instrument recognition"
    - "trainable frontend for robust and far field keyword spotting"
    - "deep convolutional networks on the pitch spiral for musical instrument recognition"

Connected through hyperedge HE-4 (induced by source paper "geometric scattering for graph data analysis"):
  with members:
    - "graph convolutional neural networks via scattering"
    - "classification with joint time frequency scattering"
    - "generative networks as inverse problems with scattering transforms"
    - "diffusion scattering transforms on graphs"
    - "how powerful are graph neural networks"
    - "covariant compositional networks for learning graphs"
    - "geometric deep learning going beyond euclidean data"
    - "graph classification with 2d convolutional neural networks"

Connected through hyperedge HE-5 (induced by source paper "kymatio scattering transforms in python"):
  with members:
    - "generative networks as inverse problems with scattering transforms"
    - "deep scattering spectrum"
    - "invariant scattering convolution networks"

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.SD(Sound)