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 "linearizing visual processes with convolutional variational autoencoders"):
  Abstract: This work studies the problem of modeling non-linear visual processes by learning linear generative models from observed sequences. We propose a joint learning framework, combining a Linear Dynamic System and a Variational Autoencoder with convolutional layers. After discussing several conditions for linearizing neural networks, we propose an architecture that allows Variational Autoencoders to simultaneously learn the non-linear observation as well as the linear state-transition from a sequence of observed frames. The proposed framework is demonstrated experimentally in three series of synthesis experiments.

Includes members:
  Member "alignment distances on systems of bags":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "dynamic variational autoencoders for visual process modeling")
  Member "dyan a dynamical atoms based network for video prediction":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "dynamic variational autoencoders for visual process modeling")
  Member "two stream convolutional networks for dynamic texture synthesis":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "intelligent home 3d automatic 3d house design from linguistic descriptions only")
  Member "dynamical textures modeling via joint video dictionary learning":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "joint learning of discriminative low dimensional image representations based on dictionary learning and two layer orthogonal projections")
  Member "visual dynamics probabilistic future frame synthesis via cross convolutional networks":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "transformation based adversarial video prediction on large scale data")
  Member "group equivariant convolutional networks":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "a permutation equivariant neural network architecture for auction design")
  Member "generating videos with scene dynamics":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "generative adversarial networks in computer vision a survey and taxonomy")
  Member "procedural generation of videos to train deep action recognition networks":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "the benefits of synthetic data for action categorization")

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.NE(Neural and Evolutionary Computing)