human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "lgn cnn a biologically inspired cnn architecture"):
  Abstract: In this paper we introduce a biologically inspired CNN architecture that has a first convolutional layer that mimics the role of the LGN. The first layer of the net shows a rotationally symmetric pattern justified by the structure of the net itself that turns up to be an approximation of a Laplacian of Gaussian. The latter function is in turn a good approximation of the receptive profiles of the cells in the LGN. The analogy with respect to the visual system structure is established, emerging directly from the architecture of the net.

Includes members:
  Member "fundamentals of recurrent neural network rnn and long short term memory lstm network":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "a cnn rnn framework for crop yield prediction")
  Member "exploiting cyclic symmetry in convolutional neural networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "on learning sets of symmetric elements")
  Member "ti pooling transformation invariant pooling for feature learning in convolutional neural networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "provably scale covariant continuous hierarchical networks based on scale normalized differential expressions coupled in cascade")
  Member "learning rotation invariant convolutional filters for texture classification":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "rest performance improvement of a black box model via rl based spatial transformation")
  Member "flip rotate pooling convolution and split dropout on convolution neural networks for image classification":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "non parametric transformation networks")
  Member "matconvnet convolutional neural networks for matlab":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "unsupervised person re identification by deep asymmetric metric embedding")

Question: Please tell me which class the source paper 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)