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 topology toolkit"
  Abstract: This system paper presents the Topology ToolKit (TTK), a software platform designed for the topological analysis of scalar data in scientific visualization. While topological data analysis has gained in popularity over the last two decades, it has not yet been widely adopted as a standard data analysis tool for end users or developers. TTK aims at addressing this problem by providing a unified, generic, efficient, and robust implementation of key algorithms for the topological analysis of scalar data, including: critical points, integral lines, persistence diagrams, persistence curves, merge trees, contour trees, Morse-Smale complexes, fiber surfaces, continuous scatterplots, Jacobi sets, Reeb spaces, and more. TTK is easily accessible to end users due to a tight integration with ParaView. It is also easily accessible to developers through a variety of bindings (Python, VTK/C++) for fast prototyping or through direct, dependency-free, C++, to ease integration into pre-existing complex systems. While developing TTK, we faced several algorithmic and software engineering challenges, which we document in this paper. In particular, we present an algorithm for the construction of a discrete gradient that complies to the critical points extracted in the piecewise-linear setting. This algorithm guarantees a combinatorial consistency across the topological abstractions supported by TTK, and importantly, a unified implementation of topological data simplification for multi-scale exploration and analysis. We also present a cached triangulation data structure, that supports time efficient and generic traversals, which self-adjusts its memory usage on demand for input simplicial meshes and which implicitly emulates a triangulation for regular grids with no memory overhead. Finally, we describe an original software architecture, which guarantees memory efficient and direct accesses to TTK features, while still allowing for researchers powerful and easy bindings and extensions. TTK is open source (BSD license) and its code. online documentation and video tutorials are available on TTK's website  [108] .

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"
    - "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"
    - "measuring distance between reeb graphs"

Connected through hyperedge HE-2 (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"
    - "local equivalence and intrinsic metrics between reeb graphs"
    - "categorified reeb graphs"
    - "computing the gromov hausdorff distance for metric trees"
    - "measuring distance between reeb graphs"

Connected through hyperedge HE-3 (induced by source paper "statistical parameter selection for clustering persistence diagrams"):
  with members:
    - "progressive wasserstein barycenters of persistence diagrams"
    - "task based augmented contour trees with fibonacci heaps"
    - "persistence atlas for critical point variability in ensembles"
    - "geometry helps to compare persistence diagrams"

Connected through hyperedge HE-4 (induced by source paper "uncertainty visualization of 2d morse complex ensembles using statistical summary maps"):
  with members:
    - "a structural average of labeled merge trees for uncertainty visualization"
    - "persistence atlas for critical point variability in ensembles"

Connected through hyperedge HE-5 (induced by source paper "topolines topological smoothing for line charts"):
  with members:
    - "at a glance pixel approximate entropy as a measure of line chart complexity"
    - "task based effectiveness of basic visualizations"

Connected through hyperedge HE-6 (induced by source paper "geometry driven detection tracking and visual analysis of viscous and gravitational fingers"):
  with members:
    - "measuring distance between reeb graphs"

Connected through hyperedge HE-7 (induced by source paper "persistence atlas for critical point variability in ensembles"):
  with members:
    - "computational complexity of the interleaving distance"
    - "sliced wasserstein kernel for persistence diagrams"
    - "geometric inference on kernel density estimates"
    - "measuring distance between reeb graphs"
    - "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.GR(Graphics)