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 "Discovering Structure in Continuous Variables Using Bayesian Networks"):
  Abstract: We study Bayesian networks for continuous variables using nonlinear conditional density estimators. We demonstrate that useful structures can be extracted from a data set in a self-organized way and we present sampling techniques for belief update based on

Includes members:
  Member "Continuous sigmoidal belief networks trained using slice sampling":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "Markov Chain Monte Carlo Methods Based on `Slicing' the Density Function")
  Member "Operations for Learning with Graphical Models decomposition techniques and the demonstration that graphical models provide":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "Update rules for parameter estimation in Bayesian networks")
  Member "A Tutorial on Learning With Bayesian Networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "Update rules for parameter estimation in Bayesian networks")

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: Probabilistic_Methods