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: "LU TP 91-25 Mass Reconstruction with a Neural Network"
  Abstract: A feed-forward neural network method is developed for reconstructing the invariant mass of hadronic jets appearing in a calorimeter. The approach is illustrated in W ! q q, where W -bosons are produced in pp reactions at SPS collider energies. The neural network method yields results that are superior to conventional methods. This neural network application differs from the classification ones in the sense that an analog number (the mass) is computed by the network, rather than a binary decision being made. As a by-product our application clearly demonstrates the need for using "intelligent" variables in instances when the amount of training instances is limited.

Connected through hyperedge HE-1 (induced by source paper "Using Neural Networks to Identify Jets"):
  with members:
    - "References "Using Neural Networks to Identify Jets", Kohonen, "Self Organized Formation of Topologically Correct Feature"
    - "LU TP 91-4 Self-organizing Networks for Extracting Jet Features"
    - "LU TP 90-3 Finding Gluon Jets with a Neural Trigger"

Connected through hyperedge HE-2 (induced by source paper "LU TP 90-3 Finding Gluon Jets with a Neural Trigger"):
  with members:
    - "References "Using Neural Networks to Identify Jets", Kohonen, "Self Organized Formation of Topologically Correct Feature"
    - "LU TP 91-4 Self-organizing Networks for Extracting Jet Features"
    - "Using Neural Networks to Identify Jets"

Connected through hyperedge HE-3 (induced by source paper "LU TP 93-13 On Langevin Updating in Multilayer Perceptrons"):
  with members:
    - "LU TP 93-24 Predicting System Loads with Artificial Neural"

Connected through hyperedge HE-4 (induced by source paper "LU TP 91-4 Self-organizing Networks for Extracting Jet Features"):
  with members:
    - "References "Using Neural Networks to Identify Jets", Kohonen, "Self Organized Formation of Topologically Correct Feature"
    - "Using Neural Networks to Identify Jets"
    - "LU TP 90-3 Finding Gluon Jets with a Neural Trigger"

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