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 "Interpretable Neural Networks with BP-SOM"):
  Abstract: Interpretation of models induced by artificial neural networks is often a difficult task. In this paper we focus on a relatively novel neural network architecture and learning algorithm, bp-som, that offers possibilities to overcome this difficulty. It is shown that networks trained with bp-som show interesting regularities, in that hidden-unit activations become restricted to discrete values, and that the som part can be exploited for automatic rule extraction.

Includes members:
  Member "Measuring the Difficulty of Specific Learning Problems":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "4 Implementing Application Specific Routines  Genetic algorithms in search, optimization, and machine learning. Reading, MA: Addison-Wesley.")
  Member "Cholinergic suppression of transmission may allow combined associative memory function and self-organization in the neocortex.":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "LEARNING TO AVOID COLLISIONS: A REINFORCEMENT LEARNING PARADIGM FOR MOBILE ROBOT NAVIGATION")
  Member "Proben1 A Set of Neural Network Benchmark Problems and Benchmarking Rules":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "Comparing Adaptive and Non-Adaptive Connection Pruning With Pure Early Stopping")
  Member "Avoiding Overfitting with BP-SOM":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "Cholinergic suppression of transmission may allow combined associative memory function and self-organization in the neocortex.")

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