human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge groups papers that share a common citing paper.

Details of the hypergraph:
Center hyperedge (induced by source paper "A self-organizing multiple-view representation of 3D objects"):
  Abstract: We explore representation of 3D objects in which several distinct 2D views are stored for each object. We demonstrate the ability of a two-layer network of thresholded summation units to support such representations. Using unsupervised Hebbian relaxation, the network learned to recognize ten objects from different viewpoints. The training process led to the emergence of compact representations of the specific input views. When tested on novel views of the same objects, the network exhibited a substantial generalization capability. In simulated psychophysical experiments, the network's behavior was qualitatively similar to that of human subjects.

Includes members:
  Member "Learning Viewpoint Invariant Representations of Faces in an Attractor Network":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "A Model of Invariant Object Recognition in the Visual System")
  Member "Implicit learning in 3D object recognition: The importance of temporal context":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "Viewpoint invariant face recognition using independent component analysis and attractor networks")
  Member "Learning Viewpoint Invariant Face Representations from Visual Experience by Temporal Association":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "Viewpoint invariant face recognition using independent component analysis and attractor networks")

Question: Please tell me which class the citing paper (i.e., the source paper of the center hyperedge) belongs to. The 7 classes are: Neural_Networks, Reinforcement_Learning, Probabilistic_Methods, Theory, Genetic_Algorithms, Case_Based, Rule_Learning. Directly output the class name.

gpt: Neural_Networks