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 "on demand solid texture synthesis using deep 3d networks"):
  Abstract: This paper describes a novel approach for on demand volumetric texture synthesis based on a deep learning framework that allows for generation of high quality 3D data at interactive rates. Based on a few example images of textures, a generative network is trained to synthesize coherent solid textures that reproduce the visual characteristics of the examples along some directions. To cope with memory limitations and computation complexity that are inherent to both high resolution and 3D processing on GPU, only 2D textures referred to as “slices” are generated during the training stage. These synthetic textures are compared to exemplar images via a perceptual loss function based on a pre-trained deep network. The proposed network is very light (less than 100k parameters), therefore it only requires sustainable training (i.e. few hours) and is capable of very fast generation (around a second for 256^3 voxels) on a single GPU. The synthesized volumes have good visual results that are at least equivalent to the state-of-the-art patch based approaches. They are naturally seamlessly tileable and can be fully generated in parallel.

Includes members:
  Member "texture mixer a network for controllable synthesis and interpolation of texture":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "gan leaks a taxonomy of membership inference attacks against gans")
  Member "non stationary texture synthesis by adversarial expansion":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "image fine grained inpainting")
  Member "stable and controllable neural texture synthesis and style transfer using histogram losses":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "collaborative distillation for ultra resolution universal style transfer")
  Member "deep image prior":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "semantic pyramid for image generation")
  Member "diversified texture synthesis with feed forward networks":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "collaborative distillation for ultra resolution universal style transfer")
  Member "two stream convolutional networks for dynamic texture synthesis":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "intelligent home 3d automatic 3d house design from linguistic descriptions only")
  Member "improved texture networks maximizing quality and diversity in feed forward stylization and texture synthesis":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "deep domain adversarial image generation for domain generalisation")
  Member "learning texture manifolds with the periodic spatial gan":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "intelligent home 3d automatic 3d house design from linguistic descriptions only")

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.GR(Graphics)