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: "bringing impressionism to life with neural style transfer in come swim"
  Abstract: Neural Style Transfer is a striking, recently-developed technique that uses neural networks to artistically redraw an image in the style of a source style image. This paper explores the use of this technique in a production setting, applying Neural Style Transfer to redraw key scenes in 'Come Swim' in the style of the impressionistic painting that inspired the film. We document how the technique can be driven within the framework of an iterative creative process to achieve a desired look, and propose a mapping of the broad parameter space to a key set of creative controls. We hope that this mapping can provide insights into priorities for future research.

Connected through hyperedge HE-1 (induced by source paper "neural style difference transfer and its application to font generation"):
  with members:
    - "automatic generation of typographic font from small font subset"
    - "a closed form solution to photorealistic image stylization"
    - "the contextual loss for image transformation with non aligned data"
    - "pyramid embedded generative adversarial network for automated font generation"
    - "contained neural style transfer for decorated logo generation"
    - "stable and controllable neural texture synthesis and style transfer using histogram losses"
    - "deep photo style transfer"
    - "auto encoder guided gan for chinese calligraphy synthesis"

Connected through hyperedge HE-2 (induced by source paper "an interaction framework for studying co creative ai"):
  with members:
    - "friend collaborator student manager how design of an ai driven game level editor affects creators"
    - "automated rationale generation a technique for explainable ai and its effects on human perceptions"
    - "co creative level design via machine learning"
    - "explainable pcgml via game design patterns"
    - "evaluating creativity in computational co creative systems"
    - "event representations for automated story generation with deep neural nets"
    - "procedural content generation via machine learning pcgml"
    - "statistical parametric speech synthesis incorporating generative adversarial networks"

Connected through hyperedge HE-3 (induced by source paper "creativebioman brain and body wearable computing based creative gaming system"):
  with members:
    - "be your own prada fashion synthesis with structural coherence"
    - "semantic style transfer and turning two bit doodles into fine artworks"
    - "a neural algorithm of artistic style"

Connected through hyperedge HE-4 (induced by source paper "neural abstract style transfer for chinese traditional painting"):
  with members:
    - "stereoscopic neural style transfer"
    - "synthesizing filamentary structured images with gans"
    - "deep photo style transfer"
    - "laplacian steered neural style transfer"
    - "unpaired image to image translation using cycle consistent adversarial networks"
    - "stylebank an explicit representation for neural image style transfer"
    - "auto painter cartoon image generation from sketch by using conditional generative adversarial networks"
    - "coherent online video style transfer"

Connected through hyperedge HE-5 (induced by source paper "a pragmatic ai approach to creating artistic visual variations by neural style transfer"):
  with members:
    - "an overview of gradient descent optimization algorithms"

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.CV(Computer Vision and Pattern Recognition)