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: "two scale topology optimization with microstructures"
  Abstract: In this paper we present a novel two-scale framework to optimize the structure and the material distribution of an object given its functional specifications. Our approach utilizes multi-material microstructures as low-level building blocks of the object. We start by precomputing the material property gamut -- the set of bulk material properties that can be achieved with all material microstructures of a given size. We represent the boundary of this material property gamut using a level set field. Next, we propose an efficient and general topology optimization algorithm that simultaneously computes an optimal object topology and spatially-varying material properties constrained by the precomputed gamut. Finally, we map the optimal spatially-varying material properties onto the microstructures with the corresponding properties in order to generate a high-resolution printable structure. We demonstrate the efficacy of our framework by designing, optimizing, and fabricating objects in different material property spaces on the level of a trillion voxels, i.e several orders of magnitude higher than what can be achieved with current systems.

Connected through hyperedge HE-1 (induced by source paper "structural design using laplacian shells"):
  with members:
    - "from 3d models to 3d prints an overview of the processing pipeline"
    - "lightweight structure design under force location uncertainty"
    - "proportional topology optimization a new non sensitivity method for solving stress constrained and minimum compliance problems and its implementation in matlab"
    - "geodesics in heat a new approach to computing distance based on heat flow"

Connected through hyperedge HE-2 (induced by source paper "design and optimization of conforming lattice structures"):
  with members:
    - "infill optimization for additive manufacturing approaching bone like porous structures"
    - "designing volumetric truss structures"
    - "lightweight structure design under force location uncertainty"

Connected through hyperedge HE-3 (induced by source paper "anisotropic multicomponent topology optimization for additive manufacturing with build orientation design and stress constrained interfaces"):
  with members:
    - "general support effective decomposition for multi directional 3d printing"

Connected through hyperedge HE-4 (induced by source paper "globally optimal joint search of topology and trajectory for planar linkages"):
  with members:
    - "functional co optimization of articulated robots"

Connected through hyperedge HE-5 (induced by source paper "one shot generation of near optimal topology through theory driven machine learning"):
  with members:
    - "geometric understanding of deep learning"
    - "infill optimization for additive manufacturing approaching bone like porous structures"
    - "adversarial attacks on neural network policies"
    - "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.CE(Computational Engineering, Finance, and Science)