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 "Bayesian Graphical Modeling for Intelligent Tutoring Systems"):
  Abstract: Conventional Intelligent Tutoring Systems (ITS) do not acknowledge uncertainty about the student's knowledge. Yet, both the outcome of any teaching intervention and the exact state of the student's knowledge are uncertain. In recent years, researchers have made startling progress in the management of uncertainty in knowledge-based systems. Building on these developments, we describe an ITS architecture that explicitly models uncertainty. This will facilitate more accurate student modeling and provide ITS's which can learn.

Includes members:
  Member "Model Selection and Accounting for Model Uncertainty in Linear Regression Models":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "Bayesian inference for nondecomposable graphical Gaussian models")
  Member "Bayesian Graphical Models for Discrete Data":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "Approximate Bayes Factors and Accounting for Model Uncertainty in Generalized Linear Models")
  Member "Introduction to the Special Section on Knowledge-Based Construction of Probabilistic and Decision Models (IEEE Transactions":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "The Automated Mapping of Plans for Plan Recognition")

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