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 "cross modal variational auto encoder with distributed latent spaces and associators"):
  Abstract: In this paper, we propose a novel structure for a cross-modal data association, which is inspired by the recent research on the associative learning structure of the brain. We formulate the cross-modal association in Bayesian inference framework realized by a deep neural network with multiple variational auto-encoders and variational associators. The variational associators transfer the latent spaces between auto-encoders that represent different modalities. The proposed structure successfully associates even heterogeneous modal data and easily incorporates the additional modality to the entire network via the proposed cross-modal associator. Furthermore, the proposed structure can be trained with only a small amount of paired data since auto-encoders can be trained by unsupervised manner. Through experiments, the effectiveness of the proposed structure is validated on various datasets including visual and auditory data.

Includes members:
  Member "variational autoencoded regression high dimensional regression of visual data on complex manifold":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "a generative map for image based camera localization")
  Member "learning to localize sound source in visual scenes":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "stavis spatio temporal audiovisual saliency network")
  Member "mix and match networks encoder decoder alignment for zero pair image translation":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "sdit scalable and diverse cross domain image translation")
  Member "speech commands a dataset for limited vocabulary speech recognition":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "on feature normalization and data augmentation")
  Member "cross modal deep variational hand pose estimation":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "rotation invariant mixed graphical model network for 2d hand pose estimation")
  Member "multimodal generative models for scalable weakly supervised learning":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "variational item response theory fast accurate and expressive")
  Member "crossing nets combining gans and vaes with a shared latent space for hand pose estimation":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "fast and accurate 3d hand pose estimation via recurrent neural network for capturing hand articulations")
  Member "conditional generation of multi modal data using constrained embedding space mapping":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "transfer learning from synthetic to real images using variational autoencoders for robotic applications")

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.LG(Machine Learning)