human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent groups of papers sharing a common citing paper.

Details of the hypergraph:
Center node: "VISOR: Schema-based Scene Analysis with Structured Neural Networks"
  Abstract: A novel approach to object recognition and scene analysis based on neural network representation of visual schemas is described. Given an input scene, the VISOR system focuses attention successively at each component, and the schema representations cooperate and compete to match the inputs. The schema hierarchy is learned from examples through unsupervised adaptation and reinforcement learning. VISOR learns that some objects are more important than others in identifying the scene, and that the importance of spatial relations varies depending on the scene. As the inputs differ increasingly from the schemas, VISOR's recognition process is remarkably robust, and automatically generates a measure of confidence in the analysis.

Connected through hyperedge HE-1 (induced by source paper "Representing and Learning Visual Schemas in Neural Networks for Scene Analysis"):
  with members:
    - "Back Propagation is Sensitive to Initial Conditions"
    - "Book Review  Introduction to the Theory of Neural Computation Reviewed by: 2"
    - "Priming, Perceptual Reversal, and Circular Reaction in a Neural Network Model of Schema-Based Vision"

Connected through hyperedge HE-2 (induced by source paper "Priming, Perceptual Reversal, and Circular Reaction in a Neural Network Model of Schema-Based Vision"):
  with members:
    - "Representing and Learning Visual Schemas in Neural Networks for Scene Analysis"

Question: Please tell me which class the center node 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