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This issue is to implement DGI for graph classification. The original DGI paper (https://arxiv.org/pdf/1809.10341.pdf) proposes a method of doing this by randomly sampling a negative graph instead of …
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### Describe the bug
In the [Deep Graph Infomax demo](https://github.com/stellargraph/stellargraph/blob/ec132647e5cf43ff683e3f2e72e18ac6daa98202/demos/embeddings/deep-graph-infomax-embeddings.ipynb…
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Hey, I trained a link prediction model, and now I want to use it to generate node embeddings. I believe training on link predictions will give me good node representations that have information on the…
rmant updated
3 years ago
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I can only find IMDB dataset of text classification, and I can't find the one you use. Can I get your original IMDB dataset？
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Hi again, I'm trying to apply NEST to my data, 3 out of five training runs has failed at the very beginning with:
Traceback (most recent call last):
File "/nfs/cellgeni/pasham/code/nest/NEST/run…
iaaka updated
6 months ago
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Hi, I am excited to see this work, and I wonder can you expose DBLP dataset and code
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I have a little doubt the Meta-path based Adjacency Matrix. Did you use metapath-based random walk? or just create the matrix by metapath schema?
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# [Roadmap]
## 1.6.1
* [x] [**`WikiCSDataset`**](https://pytorch-geometric.readthedocs.io/en/latest/modules/datasets.html#torch_geometric.datasets.WikiCS)
* [x] **`DeepGCN`**
* [x] [`GENConv…
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Dear all,
I am running the following code:
```
import torch
from IPython.display import set_matplotlib_formats
from matplotlib import pyplot as plt
import torch.nn.functional as F
#im…
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