all AI news
An ensemble of VisNet, Transformer-M, and pretraining models for molecular property prediction in OGB Large-Scale Challenge @ NeurIPS 2022. (arXiv:2211.12791v1 [cs.LG])
cs.LG updates on arXiv.org arxiv.org
In the technical report, we provide our solution for OGB-LSC 2022 Graph
Regression Task. The target of this task is to predict the quantum chemical
property, HOMO-LUMO gap for a given molecule on PCQM4Mv2 dataset. In the
competition, we designed two kinds of models: Transformer-M-ViSNet which is an
geometry-enhanced graph neural network for fully connected molecular graphs and
Pretrained-3D-ViSNet which is a pretrained ViSNet by distilling geomeotric
information from optimized structures. With an ensemble of 22 models, ViSNet
Team achieved …
arxiv challenge ensemble neurips neurips 2022 prediction property scale transformer