Molecular Knowledge Guided Prompt Adaptation for Pre-trained 2D Graph Encoders

Multimodal molecular representation and property prediction based on structured complementary feature fusion

In this work, we propose Molrep-SCF, a multimodal self-supervised pretraining framework for molecular representation learning using SMILES sequences, 2D molecular graphs, and 3D geometric structures. The three modalities are encoded using a Transformer, a graph neural network, and an invariant 3D graph neural network,...

Self-Supervised Pretraining of Molecular Graph Encoders with LeJEPA

LeJEPA is adapted to molecular graphs, evaluating GPS and Chemprop-style D-MPNN encoders on the antibiotic-activity dataset and ogbg-molhiv using a multi-seed, bootstrap-based protocol, and pretraining supplies complementary information best realised through feature-level combination, while finetuning gains are weak an...

Tri-Modality Representation Learning for Molecular Property Prediction

CrossMol: Cross-Modal Mask-Predict Pre-training For 3D Molecular Data.

MOTIVATION Self-supervised pre-training models for molecular data have demonstrated notable results across many downstream tasks. The inherent multimodal properties of molecules have also motivated efforts to capture information from different modalities. However, current multimodal molecular pre-training models usuall...

Mol-ME: Enhancing Molecular Property Prediction via Multi-Modal Alignment Learning and Ensemble Methods.

A novel multimodal alignment framework for joint modeling of molecular graphs and sequences, called Mol-ME, which employs ensemble learning to predict on extracted representations, which captures complex nonlinear relationships and compensates for the modeling limitations of single shallow networks.

Reaction-aware hypergraph learning of chemical representations with LARK

LARK is introduced, a unified framework for learning atom–molecule–reaction knowledge from chemical transformations that learns chemically informative representations of substructures involved in molecular transformations and establishes chemical transformations as a source of structured supervision for representation...