3D-GSRD: 3DMolecular Graph Auto-Encoder with Selective Re-mask Decoding

Masked graph modeling (MGM) is a promising approach for molecular representation learning (MRL). However, extending the success of re-mask decoding from 2D to 3DMGM is non-trivial, primarily due to two conflicting challenges: avoiding 2D structure leakage to the decoder, while still providing sufficient 2D context for reconstructing re-masked atoms. To address these challenges, we propose 3D-GSRD: a 3DMolecular Graph Auto-Encoder with Selective Re-mask Decoding.