Siqi Wei

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.