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: "infill optimization for additive manufacturing approaching bone like porous structures"
  Abstract: Porous structures such as trabecular bone are widely seen in nature. These structures are lightweight and exhibit strong mechanical properties. In this paper, we present a method to generate bone-like porous structures as lightweight infill for additive manufacturing. Our method builds upon and extends voxel-wise topology optimization. In particular, for the purpose of generating sparse yet stable structures distributed in the interior of a given shape, we propose upper bounds on the  localized  material volume in the proximity of each voxel in the design domain. We then aggregate the local per-voxel constraints by their  p -norm into an equivalent global constraint, in order to facilitate an efficient optimization process. Implemented on a high-resolution topology optimization framework, our results demonstrate mechanically optimized, detailed porous structures which mimic those found in nature. We further show variants of the optimized structures subject to different design specifications, and we analyze the optimality and robustness of the obtained structures.

Connected through hyperedge HE-1 (induced by source paper "design and optimization of conforming lattice structures"):
  with members:
    - "designing volumetric truss structures"
    - "two scale topology optimization with microstructures"
    - "lightweight structure design under force location uncertainty"

Connected through hyperedge HE-2 (induced by source paper "a classification of topological discrepancies in additive manufacturing"):
  with members:
    - "automated process planning for hybrid manufacturing"
    - "inferring quality in point cloud based 3d printed objects using topological data analysis"
    - "ϵ maps characterizing detecting and thickening thin features in geometric models"

Connected through hyperedge HE-3 (induced by source paper "crossfill foam structures with graded density for continuous material extrusion"):
  with members:
    - "hilbert s space filling curve for regions with holes"
    - "from 3d models to 3d prints an overview of the processing pipeline"

Connected through hyperedge HE-4 (induced by source paper "continuous toolpath planning in additive manufacturing"):
  with members:
    - "crossfill foam structures with graded density for continuous material extrusion"
    - "euler transformation of polyhedral complexes"

Connected through hyperedge HE-5 (induced by source paper "mixed projection and density based topology optimization with applications to structural assemblies"):
  with members:
    - "doing topology optimization explicitly and geometrically a new moving morphable components based framework"

Connected through hyperedge HE-6 (induced by source paper "optimal design of shell graded infill structures by a hybrid mmc mmv approach"):
  with members:
    - "doing topology optimization explicitly and geometrically a new moving morphable components based framework"

Connected through hyperedge HE-7 (induced by source paper "one shot generation of near optimal topology through theory driven machine learning"):
  with members:
    - "geometric understanding of deep learning"
    - "adversarial attacks on neural network policies"
    - "two scale topology optimization with microstructures"
    - "neural networks for topology optimization"
    - "pves position velocity encoders for unsupervised learning of structured state representations"
    - "data driven synthesis of smoke flows with cnn based feature descriptors"
    - "learning to reinforcement learn"
    - "learning to learn by gradient descent by gradient descent"

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)