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: "measuring distance between reeb graphs"
  Abstract: One of the prevailing ideas in geometric and topological data analysis is to provide descriptors that encode useful information about hidden objects from observed data. The Reeb graph is one such descriptor for a given scalar function. The Reeb graph provides a simple yet meaningful abstraction of the input domain, and can also be computed efficiently. #R##N#Given the popularity of the Reeb graph in applications, it is important to understand its stability and robustness with respect to changes in the input function, as well as to be able to compare the Reeb graphs resulting from different functions. #R##N#In this paper, we propose a metric for Reeb graphs, called the functional distortion distance. Under this distance measure, the Reeb graph is stable against small changes of input functions. At the same time, it remains discriminative at differentiating input functions. In particular, the main result is that the functional distortion distance between two Reeb graphs is bounded from below by (and thus more discriminative than) the bottleneck distance between both the ordinary and extended persistence diagrams for appropriate dimensions. #R##N#As an application of our results, we analyze a natural simplification scheme for Reeb graphs, and show that persistent features in Reeb graph remains persistent under simplification. Understanding the stability of important features of the Reeb graph under simplification is an interesting problem on its own right, and critical to the practical usage of Reeb graphs.

Connected through hyperedge HE-1 (induced by source paper "progressive wasserstein barycenters of persistence diagrams"):
  with members:
    - "persistence atlas for critical point variability in ensembles"
    - "the topology toolkit"
    - "sliced wasserstein kernel for persistence diagrams"
    - "geometry helps to compare persistence diagrams"
    - "a comparative study of efficient initialization methods for the k means clustering algorithm"

Connected through hyperedge HE-2 (induced by source paper "intrinsic interleaving distance for merge trees"):
  with members:
    - "the l cophenetic metric for phylogenetic trees as an interleaving distance"
    - "fpt algorithms for computing gromov hausdorff and interleaving distances between trees"
    - "statistical analysis and parameter selection for mapper"
    - "local equivalence and intrinsic metrics between reeb graphs"
    - "convergence between categorical representations of reeb space and mapper"
    - "categorified reeb graphs"
    - "the edit distance for reeb graphs of surfaces"

Connected through hyperedge HE-3 (induced by source paper "the l cophenetic metric for phylogenetic trees as an interleaving distance"):
  with members:
    - "computational complexity of the interleaving distance"
    - "convergence between categorical representations of reeb space and mapper"
    - "categorified reeb graphs"
    - "binary adder circuits of asymptotically minimum depth linear size and fan out two"
    - "computing the gromov hausdorff distance for metric trees"
    - "the edit distance for reeb graphs of surfaces"

Connected through hyperedge HE-4 (induced by source paper "a structural average of labeled merge trees for uncertainty visualization"):
  with members:
    - "the l cophenetic metric for phylogenetic trees as an interleaving distance"
    - "intrinsic interleaving distance for merge trees"
    - "the topology toolkit"
    - "local equivalence and intrinsic metrics between reeb graphs"
    - "categorified reeb graphs"
    - "computing the gromov hausdorff distance for metric trees"

Connected through hyperedge HE-5 (induced by source paper "metric spaces with expensive distances"):
  with members:
    - "categorified reeb graphs"
    - "the edit distance for reeb graphs of surfaces"
    - "fast construction of nets in low dimensional metrics and their applications"

Connected through hyperedge HE-6 (induced by source paper "topological feature search in time varying multifield data"):
  with members:
    - "multivariate topology simplification"

Connected through hyperedge HE-7 (induced by source paper "geometry driven detection tracking and visual analysis of viscous and gravitational fingers"):
  with members:
    - "the topology toolkit"

Connected through hyperedge HE-8 (induced by source paper "persistence atlas for critical point variability in ensembles"):
  with members:
    - "the topology toolkit"
    - "computational complexity of the interleaving distance"
    - "sliced wasserstein kernel for persistence diagrams"
    - "geometric inference on kernel density estimates"
    - "a tutorial on spectral clustering"

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)