most citedFaster and more diverse de novo molecular optimization with double-loop reinforcement learning using augmented SMILES

20 citations

researchers with a paper here

Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.

collaborating institutions

2 papers

physics.comp-ph2023

Gradient-free online learning of subgrid-scale dynamics with neural emulators

Hugo Frezat, Ronan Fablet, Guillaume Balarac +1

In this paper, we propose a generic algorithm to train machine learning-based subgrid parametrizations online, i.e., with loss functions, but for non-differ…

physics.chem-ph2022★ 20 cited

Faster and more diverse de novo molecular optimization with double-loop reinforcement learning using augmented SMILES

Esben Jannik Bjerrum, Christian Margreitter, Thomas Blaschke +1

Using generative deep learning models and reinforcement learning together can effectively generate new molecules with desired properties. By employing a multi-objective scoring fun…