d-tiapkin/gflownet-rl
Repository for "Generative Flow Networks as Entropy-Regularized RL" (AISTATS-2024, Oral)
This project provides an experimental framework for researchers to explore and develop advanced methods for generating diverse sets of outputs, such as molecules or abstract 'hypergrid' structures. It takes defined rules for how to build these outputs and produces various potential candidates. This is primarily for machine learning researchers and scientists working on generative models and reinforcement learning applications.
No commits in the last 6 months.
Use this if you are a machine learning researcher developing or evaluating new generative modeling techniques, particularly those based on Generative Flow Networks or entropy-regularized reinforcement learning.
Not ideal if you are an end-user looking for a ready-to-use tool to generate specific types of data without deep knowledge of machine learning algorithms.
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Language
Python
License
MIT
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Last pushed
Apr 21, 2024
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