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 "Representing and Learning Visual Schemas in Neural Networks for Scene Analysis"):
  Abstract: Using scene analysis as the task, this research focuses on three fundamental problems in neural network systems: (1) limited processing resources, (2) representing schemas, and (3) learning schemas. The first problem arises because no practical neural network can process all the visual input simultaneously and efficiently. The solution is to process a small amount of the input in parallel, and successively focus on the other parts of the input. This strategy requires that the system maintains structured knowledge for describing and interpreting the gathered information. The system should also learn to represent structured knowledge from examples of objects and scenes. VISOR, the system described in this paper, consists of three main components. The Low-Level Visual Module (simulated using procedural programs) extracts featural and positional information from the visual input. The Schema Module encodes structured knowledge about possible objects, and provides top-down information for the Low-Level Visual Module to focus attention at different parts of the scene. The Response Module learns to associate the schema activation patterns with external responses. It enables the external environment to provide reinforcement feedback for the learning of schematic structures.

Includes members:
  Member "Back Propagation is Sensitive to Initial Conditions":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "Neural Network Implementation in SAS R Software")
  Member "Book Review  Introduction to the Theory of Neural Computation Reviewed by: 2":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "Induction of Multiscale Temporal Structure")
  Member "Priming, Perceptual Reversal, and Circular Reaction in a Neural Network Model of Schema-Based Vision":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "VISOR: Schema-based Scene Analysis with Structured Neural Networks")
  Member "VISOR: Schema-based Scene Analysis with Structured Neural Networks":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "Priming, Perceptual Reversal, and Circular Reaction in a Neural Network Model of Schema-Based Vision")

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