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: "computing topological persistence for simplicial maps"
  Abstract: Algorithms for persistent homology and zigzag persistent homology are well-studied for persistence modules where homomorphisms are induced by inclusion maps. In this paper, we propose a practical algorithm for computing persistence under $\mathbb{Z}_2$ coefficients for a sequence of general simplicial maps and show how these maps arise naturally in some applications of topological data analysis. #R##N#First, we observe that it is not hard to simulate simplicial maps by inclusion maps but not necessarily in a monotone direction. This, combined with the known algorithms for zigzag persistence, provides an algorithm for computing the persistence induced by simplicial maps. #R##N#Our main result is that the above simple minded approach can be improved for a sequence of simplicial maps given in a monotone direction. A simplicial map can be decomposed into a set of elementary inclusions and vertex collapses--two atomic operations that can be supported efficiently with the notion of simplex annotations for computing persistent homology. A consistent annotation through these atomic operations implies the maintenance of a consistent cohomology basis, hence a homology basis by duality. While the idea of maintaining a cohomology basis through an inclusion is not new, maintaining them through a vertex collapse is new, which constitutes an important atomic operation for simulating simplicial maps. Annotations support the vertex collapse in addition to the usual inclusion quite naturally. #R##N#Finally, we exhibit an application of this new tool in which we approximate the persistence diagram of a filtration of Rips complexes where vertex collapses are used to tame the blow-up in size.

Connected through hyperedge HE-1 (induced by source paper "gpu accelerated computation of vietoris rips persistence barcodes"):
  with members:
    - "on characterizing the capacity of neural networks using algebraic topology"
    - "deep learning with topological signatures"
    - "simba an efficient tool for approximating rips filtration persistence via simplicial batch collapse"
    - "a geometric perspective on sparse filtrations"
    - "the simplex tree an efficient data structure for general simplicial complexes"
    - "the compressed annotation matrix an efficient data structure for computing persistent cohomology"

Connected through hyperedge HE-2 (induced by source paper "computing minimal persistent cycles polynomial and hard cases"):
  with members:
    - "persistent 1 cycles definition computation and its application"
    - "minimum cycle and homology bases of surface embedded graphs"
    - "approximating loops in a shortest homology basis from point data"

Connected through hyperedge HE-3 (induced by source paper "computing persistent homology with various coefficient fields in a single pass"):
  with members:
    - "the compressed annotation matrix an efficient data structure for computing persistent cohomology"

Connected through hyperedge HE-4 (induced by source paper "computing multiparameter persistent homology through a discrete morse based approach"):
  with members:
    - "persistence perfect discrete gradient vector fields and multi parameter persistence"
    - "computing discrete morse complexes from simplicial complexes"
    - "reducing complexes in multidimensional persistent homology theory"
    - "annotating simplices with a homology basis and its applications"
    - "computing multidimensional persistence"

Connected through hyperedge HE-5 (induced by source paper "the topology toolkit"):
  with members:
    - "building efficient and compact data structures for simplicial complexes"
    - "a persistence landscapes toolbox for topological statistics"
    - "the simplex tree an efficient data structure for general simplicial complexes"
    - "introduction to the r package tda"
    - "optimal topological simplification of discrete functions on surfaces"

Connected through hyperedge HE-6 (induced by source paper "filtration simplification for persistent homology via edge contraction"):
  with members:
    - "strong collapse for persistence"
    - "geometry helps to compare persistence diagrams"
    - "the theory of the interleaving distance on multidimensional persistence modules"
    - "edge contractions and simplicial homology"

Connected through hyperedge HE-7 (induced by source paper "persistent 1 cycles definition computation and its application"):
  with members:
    - "the simplex tree an efficient data structure for general simplicial complexes"
    - "the compressed annotation matrix an efficient data structure for computing persistent cohomology"
    - "approximating loops in a shortest homology basis from point data"
    - "quantifying homology classes ii localization and stability"

Connected through hyperedge HE-8 (induced by source paper "on vietoris rips complexes of planar curves"):
  with members:
    - "the persistent homotopy type distance"
    - "simba an efficient tool for approximating rips filtration persistence via simplicial batch collapse"
    - "towards persistence based reconstruction in euclidean spaces"

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)