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 "Belief Networks, Hidden Markov Models, and Markov Random Fields: a Unifying View"):
  Abstract: The use of graphs to represent independence structure in multivariate probability models has been pursued in a relatively independent fashion across a wide variety of research disciplines since the beginning of this century. This paper provides a brief overview of the current status of such research with particular attention to recent developments which have served to unify such seemingly disparate topics as probabilistic expert systems, statistical physics, image analysis, genetics, decoding of error-correcting codes, Kalman filters, and speech recognition with Markov models.

Includes members:
  Member "Exploiting Tractable Substructures in Intractable Networks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "Tractable Inference for Complex Stochastic Processes")
  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 "Probabilistic Independence Networks for Hidden Markov Probability Models":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "Tractable Inference for Complex Stochastic Processes")

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