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GraphMAE: Self-Supervised Masked Graph Autoencoders in KDD'22

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Thanks for a outstanding work, transfer learning is a very useful setup in this paper. But the performance in the table seems to require appropriate hyperparameters, can you release the...

您好,图1(b)是什么软件做出的图呀?https://github.com/THUDM/GraphMAE/blob/b14f080c919257b495e3cb6474286d5252d6a635/imgs/fig.png

Is it possible to implement Node embedding with the information about its features? After that, reconstruct the node label and features based only on the node embedding?

Dear THUDM, Firstly, I would like to express my sincere gratitude for your efforts. Your work has been immensely helpful. I have a query regarding the implementation of the inductive...

i want to use pretained model on my own dataset, could this model use on customize data.

你好,我尝试运行你的代码,但是无法下载demo数据集,请问是否有其他方法可以解决? 以下是报错 Traceback (most recent call last): File ".\main_graph.py", line 206, in main(args) File ".\main_graph.py", line 140, in main graphs, (num_features, num_classes) = load_graph_classification_dataset(dataset_name, deg4feat=deg4feat) File "F:\MYT\GraphMAE\graphmae\datasets\data_util.py", line 133, in...

Hi, I encountered a problem when reproducing the graph classification experiment. Except for the NCI1 data set, all other graph data sets can achieve the results in your paper, but...

Hi thanks for the very interesting work. I am wondering about how the metrics for the graph classification were calculated. In the paper, Table 2 is labeled at "Accuracy (%)"....