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: "anderson acceleration for geometry optimization and physics simulation"
  Abstract: We propose an effective technique to accelerate local-global solvers for geometry optimization and physics simulation by adapting Anderson Acceleration with a simple modification to improve stability and reduce overhead.

Connected through hyperedge HE-1 (induced by source paper "differentiable fixed point iteration layer"):
  with members:
    - "satnet bridging deep learning and logical reasoning using a differentiable satisfiability solver"
    - "differentiable convex optimization layers"
    - "acquisition of localization confidence for accurate object detection"
    - "deep value networks learn to evaluate and iteratively refine structured outputs"
    - "optnet differentiable optimization as a layer in neural networks"
    - "input convex neural networks"
    - "structured prediction energy networks"
    - "flownet learning optical flow with convolutional networks"

Connected through hyperedge HE-2 (induced by source paper "efficient cloth simulation using miniature cloth and upscaling deep neural networks"):
  with members:
    - "nnwarp neural network based nonlinear deformation"
    - "hierarchical cloth simulation using deep neural networks"
    - "latent space physics towards learning the temporal evolution of fluid flow"
    - "tempogan a temporally coherent volumetric gan for super resolution fluid flow"
    - "unpaired image to image translation using cycle consistent adversarial networks"
    - "accelerating eulerian fluid simulation with convolutional networks"
    - "a compositional object based approach to learning physical dynamics"
    - "unsupervised representation learning with deep convolutional generative adversarial networks"

Connected through hyperedge HE-3 (induced by source paper "accelerating admm for efficient simulation and optimization"):
  with members:
    - "parallel and scalable heat methods for geodesic distance computation"
    - "plug and play admm for image restoration fixed point convergence and applications"
    - "parallel algorithms for constrained tensor factorization via alternating direction method of multipliers"
    - "distributed maximum likelihood sensor network localization"

Connected through hyperedge HE-4 (induced by source paper "cubic stylization"):
  with members:
    - "semi supervised co analysis of 3d shape styles from projected lines"
    - "static dynamic filtering for mesh geometry"
    - "natural boundary conditions for smoothing in geometry processing"
    - "thingi10k a dataset of 10 000 3d printing models"

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.GR(Graphics)