Open access
Aug 2026
FerrGAT: Multi-Task Pre-Training of Graph Attention Networks for Low-Data Molecular Activity Prediction
FerrGAT, a graph attention network framework that addresses molecular bioactivity in low-data regimes through domain-relevant multi-task pre-training and dual-channel molecular representation learning, provides an effective and interpretable framework for molecular property prediction in data-limited scenarios.
Shichong Liu, Siqi Wei, Jian Zhao et al.
· Mathematics · 0 citations