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: "TURING COMPUTABILITY WITH NEURAL NETS"
  Abstract: This paper shows the existence of a finite neural network, made up of sigmoidal neurons, which simulates a universal Turing machine. It is composed of less than 10 5 synchronously evolving processors, interconnected linearly. High-order connections are not required.

Connected through hyperedge HE-1 (induced by source paper "On the Effect of Analog Noise in Discrete-Time Analog Computations"):
  with members:
    - "Vapnik-Chervonenkis Dimension of Recurrent Neural Networks"
    - "Constructing Deterministic Finite-State Automata in Recurrent Neural Networks"
    - "Analog Neural Nets with Gaussian or other Common Noise Distributions cannot Recognize Arbitrary Regular Languages"

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