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 "convolutional humanoid animation via deformation"):
  Abstract: In this paper we present a new deep learning-driven approach to image-based synthesis of animations involving humanoid characters. Unlike previous deep approaches to image-based animation our method makes no assumptions on the type of motion to be animated nor does it require dense temporal input to produce motion. Instead we generate new animations by interpolating between user chosen keyframes, arranged sparsely in time. Utilizing a novel configuration manifold learning approach we interpolate suitable motions between these keyframes. In contrast to previous methods, ours requires less data (animations can be generated from a single youtube video) and is broadly applicable to a wide range of motions including facial motion, whole body motion and even scenes with multiple characters. These improvements serve to significantly reduce the difficulty in producing image-based animations of humanoid characters, allowing even broader audiences to express their creativity.

Includes members:
  Member "learning symmetric and low energy locomotion":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "learning to walk in the real world with minimal human effort")
  Member "synthesizing images of humans in unseen poses":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "neural human video rendering joint learning of dynamic textures and rendering to video translation")
  Member "neural best buddies sparse cross domain correspondence":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "cross domain cascaded deep feature translation")
  Member "deepmimic example guided deep reinforcement learning of physics based character skills":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "artificial intelligence for prosthetics challenge solutions")
  Member "everybody dance now":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "gan compression efficient architectures for interactive conditional gans")
  Member "visual dynamics probabilistic future frame synthesis via cross convolutional networks":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "transformation based adversarial video prediction on large scale data")
  Member "adam a method for stochastic optimization":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "using a thousand optimization tasks to learn hyperparameter search strategies")
  Member "automatic face reenactment":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "exploiting human social cognition for the detection of fake and fraudulent faces via memory networks")

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)