  In this technical report, we present our solution of KDD Cup 2021 OGB
Large-Scale Challenge - PCQM4M-LSC Track. We adopt Graphormer and ExpC as our
basic models. We train each model by 8-fold cross-validation, and additionally
train two Graphormer models on the union of training and validation sets with
different random seeds. For final submission, we use a naive ensemble for these
18 models by taking average of their outputs. Using our method, our team
MachineLearning achieved 0.1200 MAE on test set, which won the first place in
KDD Cup graph prediction track.
