
v1.0.0 – Initial Release First stable release of the Local-Global Graph Transformer, including full model implementation, training scripts, preprocessing, and documentation. Please cite Graph Neural Networks with Hybrid Local-Global Attention for Effective Prediction of Mechanical Response in Structures, Computer Methods Applied Mechanics and Engineering, 2026. @article{patrignani2026hybrid, title={Graph Neural Networks with Hybrid Local-Global Attention for Effective Prediction of Mechanical Response in Structures}, author={Patrignani, Luca and Pinho, Silvestre T.}, journal={Computer Methods in Applied Mechanics and Engineering}, year={2026} }
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
