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 "Simple Synchrony Networks Learning to Parse Natural Language with Temporal Synchrony Variable Binding"):
  Abstract: The Simple Synchrony Network (SSN) is a new connectionist architecture, incorporating the insights of Temporal Synchrony Variable Binding (TSVB) into Simple Recurrent Networks. The use of TSVB means SSNs can output representations of structures, and can learn generalisations over the constituents of these structures (as required by systematicity). This paper describes the SSN and an associated training algorithm, and demonstrates SSNs' generalisation abilities through results from training SSNs to parse real natural language sentences.

Includes members:
  Member "A Connectionist Architecture with Inherent Systematicity":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "A Connectionist Architecture for Learning to Parse")
  Member "A Connectionist Architecture for Learning to Parse":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "A Connectionist Architecture with Inherent Systematicity")

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