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: "equivariant neural networks and equivarification"
  Abstract: We provide a process to modify a neural network to an equivariant one, which we call equivarification. As an illustration, we build an equivariant neural network for image classification by equivarifying a convolutional neural network.

Connected through hyperedge HE-1 (induced by source paper "incorporating symmetry into deep dynamics models for improved generalization"):
  with members:
    - "deep scale spaces equivariance over scale"
    - "general e 2 equivariant steerable cnns"
    - "invariant representations through adversarial forgetting"
    - "gauge equivariant convolutional networks and the icosahedral cnn"
    - "invariant representations without adversarial training"
    - "neural ordinary differential equations"
    - "learning steerable filters for rotation equivariant cnns"
    - "decomposing motion and content for natural video sequence prediction"

Connected through hyperedge HE-2 (induced by source paper "quaternion equivariant capsule networks for 3d point clouds"):
  with members:
    - "equivariant multi view networks"
    - "spherical cnns on unstructured grids"
    - "spherical regression learning viewpoints surface normals and 3d rotations on n spheres"
    - "gauge equivariant convolutional networks and the icosahedral cnn"
    - "learning an effective equivariant 3d descriptor without supervision"
    - "pointnetlk robust efficient point cloud registration using pointnet"
    - "ppfnet global context aware local features for robust 3d point matching"
    - "riemannian adaptive optimization methods"

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.LG(Machine Learning)