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: "PERFECT SIMULATION OF CONDITIONALLY SPECIFIED MODELS"
  Abstract: We discuss how the ideas of producing perfect simulations based on coupling from the past for finite state space models naturally extend to mul-tivariate distributions with infinite or uncountable state spaces such as auto-gamma, auto-Poisson and auto-negative-binomial models, using Gibbs sampling in combination with sandwiching methods originally introduced for perfect simulation of point processes.

Connected through hyperedge HE-1 (induced by source paper "Extensions of Fill's algorithm for perfect simulation"):
  with members:
    - "Perfect Simulation of some Point Processes for the Impatient User"
    - "An extension of Fill's exact sampling algorithm to non-monotone chains*"
    - "Perfect Sampling of Harris Recurrent Markov Chains"
    - "EXACT SIMULATION USING MARKOV CHAINS"

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: Probabilistic_Methods