Peer-reviewedLicence not statedIEEE Transactions on Neural Networks and Learning Systems
Geometry-Aware Line Graph Transformer Pretraining for Molecular Property Prediction
- 1University of Sheffield
- 2Zhejiang University of Technology
- 3Hong Kong Baptist University
Related
- Transfer Protocol Matters More Than Source-Task Selection in Low-Data Molecular Property Prediction: An Audit of QM9 Pretraining on Computed Oxidation Potentials and Redox Reaction Energies
- Towards Multiscale Molecular Representation Learning through Geometry-Based Fragmentation for Polymer Property Prediction
- SigmaFormer : Augmenting transformer encoders with COSMO sigma profiles for pure component property prediction
- Closed-loop Auto Research for Molecular Property Prediction: Discovering and Certifying Generalizable Improvements
- Topology-Guided Multi-Level Graph Learning: A Unified Framework for Molecular Property Prediction
BibTeX
@article{bai2026geometryaware,
title = {{Geometry-Aware Line Graph Transformer Pretraining for Molecular Property Prediction}},
author = {Peizhen Bai and Xianyuan Liu and Wenrui Fan and Tianyi Jiang and William K. Cheung and Haiping Lu},
journal = {IEEE Transactions on Neural Networks and Learning Systems},
year = {2026},
month = jun,
doi = {10.1109/tnnls.2026.3698579},
url = {http://arxiv.org/abs/2309.00483},
}
RIS
TY - JOUR
TI - Geometry-Aware Line Graph Transformer Pretraining for Molecular Property Prediction
AU - Peizhen Bai
AU - Xianyuan Liu
AU - Wenrui Fan
AU - Tianyi Jiang
AU - William K. Cheung
AU - Haiping Lu
PY - 2026
DA - 2026/06/11
JO - IEEE Transactions on Neural Networks and Learning Systems
DO - 10.1109/tnnls.2026.3698579
UR - http://arxiv.org/abs/2309.00483
SN - 2162-237X
SN - 2162-2388
ER -