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Hi ,great work!
when I run
```
prior_network = pd.read_csv('./network_mouse.csv')
data = cf.data_preparation(adata, prior_network)
[0] - Data loading and preprocessing...
Consider the input data…
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## Description
As reported in https://community.stellargraph.io/t/valueerror-if-specifying-tensorspec-names-for-nested-structures-either-zero-or-all-names-have-to-be-specified/97, saving some model…
huonw updated
4 years ago
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### 🐛 Describe the bug
when updating from 8c849a482c3cf2326c1f493e79d04169b26dfb0b to the latest commit c0c2d5fefddbce412741db68cc7a74af225fa94a
we now see the following errors (their all pretty muc…
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I don't manage to make the "Node representation learning with Deep Graph Infomax" demo work. I would especially like to **extract the embeddings**.
I downloaded the notebook locally from the demo p…
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### Describe the bug
I have follwing graph:
```
StellarDiGraph: Directed multigraph
Nodes: 1911, Edges: 2483
Node types:
Segment: [670]
Features: float32 vector, length 1861
E…
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## 🐛 Bug
How the data.y was generated? Did optimize model with y is not self-supervis…
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I have a multi-partite heterogeneous graph with 4 node types. I am trying to do something like this demo: https://stellargraph.readthedocs.io/en/stable/demos/embeddings/graphsage-unsupervised-sampler-…
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Example: https://mila.quebec/en/publications/
It would be nice to reuse the same code as in the Mila website. Not sure if that's 'easily' possible via RTD
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An example of applying Deep Graph Infomax on heterogeneous graphs.