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Hello,
I am a novice at using ML techniques like this, so forgive me for the simplistic question. I have been trying to apply the parameters given in your jupyter notebooks to my system and coming …
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```
using GraphNeuralNetworks
g = GNNGraph()
add_nodes(g, 5)
@info "GRAPH WITH UNCONNECTED NODES" g
add_edges(g, [1, 2], [3, 4])
@info "GRAPH WITH SOME CONNECTED NODES" g
```
```
…
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Hello, many thanks for a great package.
My task can be summarised as graph classification, where (i) multiple graphs are associated with a common label, and where (ii) all graphs have the same str…
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Currently we pass many configs explicitly through the various models, into molecule_graph_model, and onto GraphNeuralNetwork. Probably this could be simplified with kwargs.
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I see the following warning while precompiling the package:
```
WARNING: Method definition (::GraphNeuralNetworks.GINConv{R
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**Describe the bug 🐞**
I'm trying to train a Graph NODE integrating `GraphNeuralNetworks.jl` with `OrdinaryDiffEq.jl` where I am learning not only the weights of the neural network, but also the ed…
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Hello, just found your sweet package!
I ran into a minor issue when wrapping a SimpleWeightedDiGraph with a GNNGraph. The weights from the DiGraph are not included in the wrapped graph.
Below is …
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As discussed in the closed PR https://github.com/CarloLucibello/GraphNeuralNetworks.jl/pull/376, I investigated the reason why `MLUtils.unbatch` did not work on the GPU. I found out that it uses `geto…
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Given example:
```julia
using Flux, GraphNeuralNetworks, CUDA
data = [[2,3], [1,4,5], [1], [2,5], [2,4]]
g = GNNGraph(data)
g.num_nodes # 5
g.num_edges # 10
g.num_graphs # 1
s = [1,1…
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The following snippet causes scalar indexing error on GPU, which is reproducible on the latest release and the master branch.
```julia
using CUDA
using Flux
using GraphNeuralNetworks
CUDA.allow…