ActiveFusion: Fused Representations Improve Active Learning for Molecular Property Prediction
This work introduces ActiveFusion, a framework for integrating heterogeneous molecular representations within active learning workflows for molecular property prediction and offers practical guidance for designing active learning pipelines that balance prediction accuracy with chemical space exploration.