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 "imaginenet restyling apps using neural style transfer"):
  Abstract: This paper presents ImagineNet, a tool that uses a novel neural style transfer model to enable end-users and app developers to restyle GUIs using an image of their choice. Former neural style transfer techniques are inadequate for this application because they produce GUIs that are illegible and hence nonfunctional. We propose a neural solution by adding a new loss term to the original formulation, which minimizes the squared error in the uncentered cross-covariance of features from different levels in a CNN between the style and output images. ImagineNet retains the details of GUIs, while transferring the colors and textures of the art. We presented GUIs restyled with ImagineNet as well as other style transfer techniques to 50 evaluators and all preferred those of ImagineNet. We show how ImagineNet can be used to restyle (1) the graphical assets of an app, (2) an app with user-supplied content, and (3) an app with dynamically generated GUIs.

Includes members:
  Member "a closed form solution to photorealistic image stylization":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "learning texture invariant representation for domain adaptation of semantic segmentation")
  Member "learning linear transformations for fast arbitrary style transfer":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "style transfer for light field photography")
  Member "demystifying neural style transfer":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "centrality graph convolutional networks for skeleton based action recognition")
  Member "arbitrary style transfer in real time with adaptive instance normalization":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "π nets deep polynomial neural networks")
  Member "photorealistic style transfer with screened poisson equation":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "animating landscape self supervised learning of decoupled motion and appearance for single image video synthesis")
  Member "deep photo style transfer":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "parameter free style projection for arbitrary style transfer")
  Member "visual attribute transfer through deep image analogy":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "collaborative distillation for ultra resolution universal style transfer")
  Member "universal style transfer via feature transforms":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "collaborative distillation for ultra resolution universal style transfer")

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.CV(Computer Vision and Pattern Recognition)