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 "Equivalence of Linear Boltzmann Chains and Hidden Markov Models sequence L, is: where Z(; A;"):
  Abstract: Several authors have made a link between hidden Markov models for time series and energy-based models (Luttrell 1989, Williams 1990, Saul and Jordan 1995). Saul and Jordan (1995) discuss a linear Boltzmann chain model with state-state transition energies A ii 0 (going from state i to state i 0 ) and symbol emission energies B ij , under which the probability of an entire state fi l ; j l g L Whilst any HMM can be written as a linear Boltzmann chain by setting exp(A ii 0 ) = a ii 0 , exp(B ij ) = b ij and exp( i ) = i , not all linear Boltzmann chains can be represented as HMMs (Saul and Jordan 1995). However, the difference between the two models is minimal. To be precise, if the final hidden

Includes members:
  Member "GIBBS-MARKOV MODELS":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "Hidden Markov Models in Computational Biology: Applications to Protein Modeling UCSC-CRL-93-32 Keywords: Hidden Markov Models,")
  Member "GIBBS-MARKOV MODELS":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "Hidden Markov Models in Computational Biology: Applications to Protein Modeling UCSC-CRL-93-32 Keywords: Hidden Markov Models,")
  Member "GIBBS-MARKOV MODELS":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "Hidden Markov Models in Computational Biology: Applications to Protein Modeling UCSC-CRL-93-32 Keywords: Hidden Markov Models,")
  Member "Learning networks for face analysis and synthesis":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "Receptive Fields for Vision: from Hyperacuity to Object Recognition")
  Member "Boltzmann Chains and Hidden Markov Models":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "Learning in Boltzmann Trees")

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