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Hello,
Thank you for sharing the code for A-2Q!
I'm interested in applying A-2Q to heterogeneous graphs, specifically using RGCNs. I've replaced the standard Linear layers with your provided QLine…
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### 🚀 The feature, motivation and pitch
Explainability is a key feature of GNNs, which is already implemented in PyG. However, of all the features introduced, only a few have been adapted to heteroge…
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This model can be used to classify nodes of heterogeneous graphs. How effective is it
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Description:
The to_pyg_data method currently only supports homogeneous graphs and a single feature. It would be great if this method could also handle heterogeneous graphs and support multiple f…
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### 🐛 Describe the bug
After several failed attempts to create a Heterogeneous Graph AutoEncoder It's time to ask for help.
Here is a sample of my Dataset:
```
====================
Number of …
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I would like to request this paper as a method for OpenHGNN:
https://arxiv.org/abs/2208.09957
Best,
Nicolai
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### 🚀 The feature, motivation and pitch
When creating a heterogeneous model by using `torch_geometric.nn.to_hetero_with_bases()`, using `torch.nn.parameter.Parameter` directly as a layer is unsupport…
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Hi,
Thanks for making the source of HGT public.
A question that I have is that how can we use HGT to classify heterogeneous graphs?
Currently, the training examples that are provided are for node…
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Hi,
I am trying to apply pyg_autoscale to heterogeneous graph and have to modify the compute_subgraph method in SubgraphLoader class. I was wondering would you like to elaborate on what `offset`, `c…
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Any ideas on how to extend this to graphs with different types of nodes? Thanks!