Introduction Generative Flow Networks are an emerging framework in deep learning that offers a novel approach to generating diverse and high-quality samples from structured probability distributions. Unlike traditional generative models such as GANs and VAEs, applications of gflownets in machine learning focus on generating samples proportionally to a given reward function, enabling efficient exploration of