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: "the varifold representation of nonoriented shapes for diffeomorphic registration"
  Abstract: In this paper, we address the problem of orientation that naturally arises when representing shapes such as curves or surfaces as currents. In the field of computational anatomy, the framework of currents has indeed proved very efficient in modeling a wide variety of shapes. However, in such approaches, orientation of shapes is a fundamental issue that can lead to several drawbacks in treating certain kinds of datasets. More specifically, problems occur with structures like acute pikes because of canceling effects of currents or with data that consists in many disconnected pieces like fiber bundles for which currents require a consistent orientation of all pieces. As a promising alternative to currents, varifolds, introduced in the context of geometric measure theory by Almgren, allow the representation of any nonoriented manifold (more generally any nonoriented rectifiable set). In particular, we explain how varifolds can encode numerically nonoriented objects both from the discrete and the continuous po...

Connected through hyperedge HE-1 (induced by source paper "white matter fiber analysis using kernel dictionary learning and sparsity priors"):
  with members:
    - "white matter fiber segmentation using functional varifolds"
    - "the fshape framework for the variability analysis of functional shapes"

Connected through hyperedge HE-2 (induced by source paper "3d normal coordinate systems for cortical areas"):
  with members:
    - "computational anatomy in theano"

Connected through hyperedge HE-3 (induced by source paper "learning distributions of shape trajectories from longitudinal datasets a hierarchical model on a manifold of diffeomorphisms"):
  with members:
    - "parallel transport in shape analysis a scalable numerical scheme"

Connected through hyperedge HE-4 (induced by source paper "white matter fiber segmentation using functional varifolds"):
  with members:
    - "the fshape framework for the variability analysis of functional shapes"

Connected through hyperedge HE-5 (induced by source paper "a diffeomorphic approach to multimodal registration with mutual information applications to clarity mouse brain images"):
  with members:
    - "the open connectome project data cluster scalable analysis and vision for high throughput neuroscience"

Connected through hyperedge HE-6 (induced by source paper "geodesic exponential kernels when curvature and linearity conflict"):
  with members:
    - "kernel methods on riemannian manifolds with gaussian rbf kernels"
    - "kernel methods on the riemannian manifold of symmetric positive definite matrices"
    - "optimizing over radial kernels on compact manifolds"
    - "shortest path distance in random k nearest neighbor graphs"

Connected through hyperedge HE-7 (induced by source paper "the fshape framework for the variability analysis of functional shapes"):
  with members:
    - "functional currents a new mathematical tool to model and analyse functional shapes"

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.CG(Computational Geometry)