AI for Drug Discovery
Marianna Rapsomaniki, Jannis Born, et al.
AMLD EPFL 2024
With the growing availability of data within various scientific domains, generative models hold enormous potential to accelerate scientific discovery. They harness powerful representations learned from datasets to speed up the formulation of novel hypotheses with the potential to impact material discovery broadly. We present the Generative Toolkit for Scientific Discovery (GT4SD). This extensible open-source library enables scientists, developers, and researchers to train and use state-of-the-art generative models to accelerate scientific discovery focused on organic material design.
Marianna Rapsomaniki, Jannis Born, et al.
AMLD EPFL 2024
Jannis Born, Matteo Manica
Nature Machine Intelligence
Baifeng Shi, Judy Hoffman, et al.
NeurIPS 2020
Weixin Liang, Girmaw Abebe Tadesse, et al.
Nature Machine Intelligence