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: "fast wavenet generation algorithm"
  Abstract: This paper presents an efficient implementation of the Wavenet generation process called Fast Wavenet. Compared to a naive implementation that has complexity O(2^L) (L denotes the number of layers in the network), our proposed approach removes redundant convolution operations by caching previous calculations, thereby reducing the complexity to O(L) time. Timing experiments show significant advantages of our fast implementation over a naive one. While this method is presented for Wavenet, the same scheme can be applied anytime one wants to perform autoregressive generation or online prediction using a model with dilated convolution layers. The code for our method is publicly available.

Connected through hyperedge HE-1 (induced by source paper "hierarchical autoregressive image models with auxiliary decoders"):
  with members:
    - "preventing posterior collapse with delta vaes"
    - "the challenge of realistic music generation modelling raw audio at scale"
    - "deep contextualized word representations"
    - "large scale gan training for high fidelity natural image synthesis"
    - "autoregressive quantile networks for generative modeling"
    - "bert pre training of deep bidirectional transformers for language understanding"
    - "a style based generator architecture for generative adversarial networks"
    - "generating high fidelity images with subscale pixel networks and multidimensional upscaling"

Connected through hyperedge HE-2 (induced by source paper "waveflow a compact flow based model for raw audio"):
  with members:
    - "fastspeech fast robust and controllable text to speech"
    - "parallel neural text to speech"
    - "high fidelity speech synthesis with adversarial networks"
    - "discrete flows invertible generative models of discrete data"
    - "flow improving flow based generative models with variational dequantization and architecture design"
    - "emerging convolutions for generative normalizing flows"
    - "blow a single scale hyperconditioned flow for non parallel raw audio voice conversion"
    - "the challenge of realistic music generation modelling raw audio at scale"

Connected through hyperedge HE-3 (induced by source paper "gansynth adversarial neural audio synthesis"):
  with members:
    - "augmented cyclic adversarial learning for low resource domain adaptation"
    - "a multi discriminator cyclegan for unsupervised non parallel speech domain adaptation"
    - "sing symbol to instrument neural generator"
    - "spectral normalization for generative adversarial networks"
    - "large scale gan training for high fidelity natural image synthesis"
    - "adversarial audio synthesis"
    - "a style based generator architecture for generative adversarial networks"
    - "on convergence and stability of gans"

Connected through hyperedge HE-4 (induced by source paper "adversarial generation of time frequency features with application in audio synthesis"):
  with members:
    - "gansynth adversarial neural audio synthesis"
    - "a context encoder for audio inpainting"
    - "speech commands a dataset for limited vocabulary speech recognition"
    - "large scale gan training for high fidelity natural image synthesis"
    - "timbretron a wavenet cyclegan cqt audio pipeline for musical timbre transfer"
    - "adversarial audio synthesis"
    - "improving dnn based music source separation using phase features"
    - "gans trained by a two time scale update rule converge to a nash equilibrium"

Connected through hyperedge HE-5 (induced by source paper "learning a spatio temporal embedding for video instance segmentation"):
  with members:
    - "video instance segmentation"
    - "nuscenes a multimodal dataset for autonomous driving"
    - "mots multi object tracking and segmentation"
    - "maskrnn instance level video object segmentation"
    - "path aggregation network for instance segmentation"
    - "tracking emerges by colorizing videos"
    - "towards a principled integration of multi camera re identification and tracking through optimal bayes filters"
    - "recurrent pixel embedding for instance grouping"

Connected through hyperedge HE-6 (induced by source paper "classical music generation in distinct dastgahs with alimnet acgan"):
  with members:
    - "instrument independent dastgah recognition of iranian classical music using azarnet"
    - "midinet a convolutional generative adversarial network for symbolic domain music generation"
    - "a report on sound event detection with different binaural features"
    - "convolutional recurrent neural networks for polyphonic sound event detection"
    - "neural audio synthesis of musical notes with wavenet autoencoders"
    - "svsgan singing voice separation via generative adversarial network"
    - "tac gan text conditioned auxiliary classifier generative adversarial network"
    - "neural discrete representation learning"

Connected through hyperedge HE-7 (induced by source paper "the effect of explicit structure encoding of deep neural networks for symbolic music generation"):
  with members:
    - "counterpoint by convolution"
    - "neural style transfer for audio spectograms"
    - "imposing higher level structure in polyphonic music generation using convolutional restricted boltzmann machines and constraints"
    - "music style transfer issues a position paper"
    - "parallel wavenet fast high fidelity speech synthesis"
    - "neural audio synthesis of musical notes with wavenet autoencoders"
    - "deep learning techniques for music generation a survey"
    - "a unit selection methodology for music generation using deep neural networks"

Connected through hyperedge HE-8 (induced by source paper "midinet a convolutional generative adversarial network for symbolic domain music generation"):
  with members:
    - "composing music with grammar argumented neural networks and note level encoding"
    - "neural audio synthesis of musical notes with wavenet autoencoders"
    - "nips 2016 tutorial generative adversarial networks"
    - "a unit selection methodology for music generation using deep neural networks"
    - "conditional image generation with pixelcnn decoders"
    - "samplernn an unconditional end to end neural audio generation model"
    - "improved techniques for training gans"
    - "generative adversarial text to image synthesis"

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)