The processing of chemical information by computational intelligence methods faces the challenge of the structural complexity of molecular graphs. These graphs are not amenable to being represented in ...

Molecular property prediction plays a crucial role in drug development and materials science. Traditional experimental methods are costly, time-consuming, and risky, while deep learning technologies ...

Additionally, log-RRIM employs a local-to-global graph transformer-based reaction representation learning process, which first learns representations at the molecule level for each component ...

Equivariant Masked Position Prediction for Efficient Molecular Representation This is the official code-release for the paper Equivariant Masked Position Prediction for Efficient Molecular ...