Calculating Expectation Values in Spinfoams using Machine LearningConfirmed

by Athanasios Kogios (Perimeter Institute for Theoretical Physics)

Monday Dec 2, 2024, 2:00 p.m. → 2:30 p.m. America/Toronto

PI/4-400 - Space Room (Perimeter Institute for Theoretical Physics)

Following recent advances in using machine learning algorithms for speeding up computations, we employ the newly proposed Generative Flow Networks as an alternative to traditional Markov Chain Monte Carlo methods for the calculation of expectation values of observables in the spinfoam framework.