2 code implementations • 19 Sep 2023 • Mohammad-Javad Darvishi-Bayazi, Mohammad Sajjad Ghaemi, Timothee Lesort, Md Rifat Arefin, Jocelyn Faubert, Irina Rish
We see improvement in the performance of the target model on the target (NMT) datasets by using the knowledge from the source dataset (TUAB) when a low amount of labelled data was available.
no code implementations • 21 Feb 2023 • Mohammad Sajjad Ghaemi, Hang Hu, Anguang Hu, Hsu Kiang Ooi
The continuous property of the latent space, which characterizes the discrete chemical structures, provides a flexible representation for inverse design in order to discover novel molecules.
no code implementations • 21 Feb 2023 • Hang Hu, Hsu Kiang Ooi, Mohammad Sajjad Ghaemi, Anguang Hu
Drug discovery is a complex process with a large molecular space to be considered.
no code implementations • 5 Apr 2022 • Mohammad Sajjad Ghaemi, Karl Grantham, Isaac Tamblyn, Yifeng Li, Hsu Kiang Ooi
Deploying generative machine learning techniques to generate novel chemical structures based on molecular fingerprint representation has been well established in molecular design.