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: "bifurcation spiking neural network"
  Abstract: Recently spiking neural networks (SNNs) have received much attention because of its rich biological significance and its power in processing spatial and temporal information. However, most existing SNNs are static due to the fixed eigenvalues of spiking generation functions, which means that neurons fire spikes in a fixed frequency when receiving constant input signals. Thereby, the static SNNs are limited in scalability. In this paper, we clarify the bifurcation relationship that dynamic eigenvalues have a great influence on the neuron excitation frequency. And then we propose the Bifurcation Spiking Neural Network (BSNN) for developing a dynamic SNN. Different from traditional static SNNs, BSNN takes a bifurcation system with time-varying eigenvalues as the basic building block, thus it has more powerful flexibility and is able to handle data with complex nonlinear structures. Experiments on wide-range tasks have been conducted, including a delayed-memory XOR task, four image recognition datasets, and 25 UCR archive. The results show that the performance of BSNN is superior to the existing static SNN models.

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.NE(Neural and Evolutionary Computing)