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 "neural drum machine an interactive system for real time synthesis of drum sounds"):
  Abstract: In this work, we introduce a system for real-time generation of drum sounds. This system is composed of two parts: a generative model for drum sounds together with a Max4Live plugin providing intuitive controls on the generative process. The generative model consists of a Conditional Wasserstein autoencoder (CWAE), which learns to generate Mel-scaled magnitude spectrograms of short percussion samples, coupled with a Multi-Head Convolutional Neural Network (MCNN) which estimates the corresponding audio signal from the magnitude spectrogram. The design of this model makes it lightweight, so that it allows one to perform real-time generation of novel drum sounds on an average CPU, removing the need for the users to possess dedicated hardware in order to use this system. We then present our Max4Live interface designed to interact with this generative model. With this setup, the system can be easily integrated into a studio-production environment and enhance the creative process. Finally, we discuss the advantages of our system and how the interaction of music producers with such tools could change the way drum tracks are composed.

Includes members:
  Member "variation network learning high level attributes for controlled input manipulation":
    also connected through other hyperedges:
      (none)
  Member "fast spectrogram inversion using multi head convolutional neural networks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "ddsp differentiable digital signal processing")
  Member "waveglow a flow based generative network for speech synthesis":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "videoflow a conditional flow based model for stochastic video generation")
  Member "generative timbre spaces regularizing variational auto encoders with perceptual metrics":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "classical music prediction and composition by means of variational autoencoders")
  Member "timbretron a wavenet cyclegan cqt audio pipeline for musical timbre transfer":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "deep learning for audio signal processing")
  Member "adversarial audio synthesis":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "ddsp differentiable digital signal processing")
  Member "comparison of time frequency representations for environmental sound classification using convolutional neural networks":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "applying visual domain style transfer and texture synthesis techniques to audio insights and challenges")
  Member "checkerboard artifact free sub pixel convolution a note on sub pixel convolution resize convolution and convolution resize":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "fisheyedistancenet self supervised scale aware distance estimation using monocular fisheye camera for autonomous driving")

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.SD(Sound)