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 "quaternion equivariant capsule networks for 3d point clouds"):
  Abstract: We present a 3D capsule architecture for processing of point clouds that is equivariant with respect to the $SO(3)$ rotation group, translation and permutation of the unordered input sets. The network operates on a sparse set of local reference frames, computed from an input point cloud and establishes end-to-end equivariance through a novel 3D quaternion group capsule layer, including an equivariant dynamic routing procedure. The capsule layer enables us to disentangle geometry from pose, paving the way for more informative descriptions and a structured latent space. In the process, we theoretically connect the process of dynamic routing between capsules to the well-known Weiszfeld algorithm, a scheme for solving \emph{iterative re-weighted least squares (IRLS)} problems with provable convergence properties, enabling robust pose estimation between capsule layers. Due to the sparse equivariant quaternion capsules, our architecture allows joint object classification and orientation estimation, which we validate empirically on common benchmark datasets.

Includes members:
  Member "equivariant multi view networks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "multiview aggregation for learning category specific shape reconstruction")
  Member "spherical cnns on unstructured grids":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "silhonet fisheye adaptation of a roi based object pose estimation network to monocular fisheye images")
  Member "spherical regression learning viewpoints surface normals and 3d rotations on n spheres":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "enabling viewpoint learning through dynamic label generation")
  Member "gauge equivariant convolutional networks and the icosahedral cnn":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "on learning sets of symmetric elements")
  Member "learning an effective equivariant 3d descriptor without supervision":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "lrf net learning local reference frames for 3d local shape description and matching")
  Member "pointnetlk robust efficient point cloud registration using pointnet":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "a rotation invariant framework for deep point cloud analysis")
  Member "equivariant neural networks and equivarification":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "incorporating symmetry into deep dynamics models for improved generalization")
  Member "ppfnet global context aware local features for robust 3d point matching":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "3d point cloud processing and learning for autonomous driving")

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.LG(Machine Learning)