RGFN: Synthesizable Molecular Generation Using GFlowNets
M Koziarski, A Rekesh, D Shevchuk… - arXiv preprint arXiv …, 2024 - arxiv.org
Generative models hold great promise for small molecule discovery, significantly increasing
the size of search space compared to traditional in silico screening libraries. However, most …
the size of search space compared to traditional in silico screening libraries. However, most …
Active Learning Enables Extrapolation in Molecular Generative Models
Although generative models hold promise for discovering molecules with optimized desired
properties, they often fail to suggest synthesizable molecules that improve upon the known …
properties, they often fail to suggest synthesizable molecules that improve upon the known …
Generative Topological Networks
A Levy-Jurgenson, Z Yakhini - arXiv preprint arXiv:2406.15152, 2024 - arxiv.org
Generative models have seen significant advancements in recent years, yet often remain
challenging and costly to train and use. We introduce Generative Topological Networks …
challenging and costly to train and use. We introduce Generative Topological Networks …