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 iisignature library efficient calculation of iterated integral signatures and log signatures"
  Abstract: Iterated-integral signatures and log signatures are vectors calculated from a path that characterise its shape. They come from the theory of differential equations driven by rough paths, and also have applications in statistics and machine learning. We present algorithms for efficiently calculating these signatures, and benchmark their performance. We release the methods as a Python package.

Connected through hyperedge HE-1 (induced by source paper "signatory differentiable computations of the signature and logsignature transforms on both cpu and gpu"):
  with members:
    - "deep signature transforms"
    - "learning stochastic differential equations using rnn with log signature features"
    - "deepwriterid an end to end online text independent writer identification system"

Connected through hyperedge HE-2 (induced by source paper "learning stochastic differential equations using rnn with log signature features"):
  with members:
    - "ntu rgb d 120 a large scale benchmark for 3d human activity understanding"
    - "skeleton based gesture recognition using several fully connected layers with path signature features and temporal transformer module"
    - "neural ordinary differential equations"
    - "skeleton based human action recognition with global context aware attention lstm networks"
    - "modeling temporal dynamics and spatial configurations of actions using two stream recurrent neural networks"
    - "skeleton based action recognition using spatio temporal lstm network with trust gates"
    - "beyond finite layer neural networks bridging deep architectures and numerical differential equations"
    - "developing the path signature methodology and its application to landmark based human action recognition"

Connected through hyperedge HE-3 (induced by source paper "deep signature transforms"):
  with members:
    - "signatory differentiable computations of the signature and logsignature transforms on both cpu and gpu"
    - "developing the path signature methodology and its application to landmark based human action recognition"
    - "learning spatial semantic context with fully convolutional recurrent network for online handwritten chinese text recognition"
    - "dropsample a new training method to enhance deep convolutional neural networks for large scale unconstrained handwritten chinese character recognition"
    - "generative moment matching networks"
    - "deepwriterid an end to end online text independent writer identification system"
    - "adam a method for stochastic optimization"

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.DS(Data Structures and Algorithms)