GRAND
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Source code and dataset of the NeurIPS 2020 paper "Graph Random Neural Network for Semi-Supervised Learning on Graphs"
Bumps [numpy](https://github.com/numpy/numpy) from 1.16.4 to 1.22.0. Release notes Sourced from numpy's releases. v1.22.0 NumPy 1.22.0 Release Notes NumPy 1.22.0 is a big release featuring the work of 153 contributors spread...
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Hi, I tried to run the code. However, it seems that requirements are not compatible with python 3.6, 3.7, and 3.8 and I got conflicts. Would you plz export your...
In the paper, you come to the conclusion that dropout’s regularization term is the upper bound of DropNode’s with the Cauchy-Schwarz Inequality in 3.3. But the two fomulas are like...
I wonder if you can add an OGB experiment result? I tried to run GRAND on the ogbn-arXiv dataset, but the result was very bad.
In the Appendix the auther reported the performance of GRAND when the label rate is small. Can you show me the detail hyperparameters when the label rate is small?
I noticed that the backbone model used for the regularization based GNNs is GCN. While GRAND seems to use a mixed-order propagation backbone. Is this a fair comparison? I wonder...
Why apply row normalization on the raw node feature before training? This procedure is not mentioned in the paper. And I find if we remove this normalization procedure for data...
Bumps [scipy](https://github.com/scipy/scipy) from 1.3.0 to 1.10.0. Release notes Sourced from scipy's releases. SciPy 1.10.0 Release Notes SciPy 1.10.0 is the culmination of 6 months of hard work. It contains many...
Hello Author. We are concerned that you have constructed the Aminer-CS dataset by extracting citations from Aminer. We are currently trying to study academic networks, can you describe the construction...
