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 "modeling melodic feature dependency with modularized variational auto encoder"):
  Abstract: Automatic melody generation has been a long-time aspiration for both AI researchers and musicians. However, learning to generate euphonious melodies has turned out to be highly challenging. This paper introduces 1) a new variant of variational autoencoder (VAE), where the model structure is designed in a modularized manner in order to model polyphonic and dynamic music with domain knowledge, and 2) a hierarchical encoding/decoding strategy, which explicitly models the dependency between melodic features. The proposed framework is capable of generating distinct melodies that sounds natural, and the experiments for evaluating generated music clips show that the proposed model outperforms the baselines in human evaluation.

Includes members:
  Member "bachprop learning to compose music in multiple styles":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "learning to generate music with bachprop")
  Member "convolutional generative adversarial networks with binary neurons for polyphonic music generation":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "dawson a domain adaptive few shot generation framework")
  Member "deepj style specific music generation":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "mg vae deep chinese folk songs generation with specific regional styles")
  Member "a hierarchical latent vector model for learning long term structure in music":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "music generation by deep learning challenges and directions")
  Member "midinet a convolutional generative adversarial network for symbolic domain music generation":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "music generation by deep learning challenges and directions")
  Member "jambot music theory aware chord based generation of polyphonic music with lstms":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "symbolic music genre transfer with cyclegan")
  Member "neural audio synthesis of musical notes with wavenet autoencoders":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "ddsp differentiable digital signal processing")
  Member "seqgan sequence generative adversarial nets with policy gradient":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "generative adversarial networks in computer vision a survey and taxonomy")

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.AI(Artificial Intelligence)