Releases: JuliaGraphs/GraphNeuralNetworks.jl
Releases · JuliaGraphs/GraphNeuralNetworks.jl
v0.4.1
GraphNeuralNetworks v0.4.1
Closed issues:
Merged pull requests:
- SGConv (#154) (@rbSparky)
- support for MLDatasets v0.6 (#164) (@CarloLucibello)
v0.4.0
GraphNeuralNetworks v0.4.0
Closed issues:
- hope can load dataset with GraphMLDatasets.jl (#149)
- GPU memory filling up (#150)
- Citing GraphNeuralNetworks.jl (#151)
Merged pull requests:
- Citing (#152) (@CarloLucibello)
- MLUtils and Flux v0.13 compatibility (#155) (@CarloLucibello)
v0.3.15
GraphNeuralNetworks v0.3.15
Merged pull requests:
- better printing for GNNGraphs and check that features are arrays (#145) (@CarloLucibello)
- Added GMMConv (#147) (@melioristic)
- Update conv.md (#148) (@melioristic)
v0.3.14
GraphNeuralNetworks v0.3.14
Closed issues:
- Explainer vs GeometricFlux (#81)
- Gradient of edge weights is nothing with fused e_mul_xj (#113)
- Roadmap to merge GeometricFlux.jl and GraphNeuralNetworks.jl (#132)
- Failed to compile PTX code (#133)
- GINConv not working on GPU when not all nodes are connected (#138)
- Batchnorm for Integers after GCNConv or GINConv on GPU (#140)
- Slow interaction with DataLoader (#141)
Merged pull requests:
- differentiable adjacency_matrix and degree (#123) (@CarloLucibello)
- remove cast rrule not needed anymore (#135) (@CarloLucibello)
- handle isolated nodes (#139) (@CarloLucibello)
- dataloader support for vector of graphs (#143) (@CarloLucibello)
v0.3.13
GraphNeuralNetworks v0.3.13
Closed issues:
- Failure to combine
SparseDiffTools.autoback_hesvec
andGCNConv
(#125) - Support edge attributes in as many layers as possible (#128)
Merged pull requests:
- Improve support in conv layers for edge features (#130) (@CarloLucibello)
- GATv2 fix with edge features + doc improves (#131) (@CarloLucibello)
v0.3.12
GraphNeuralNetworks v0.3.12
Closed issues:
- batching scales quadratically (#99)
- aggregate_neighbors() is 100x slower than equivalent sparse matrix operation (#124)
- GATv2Conv show method errors (#126)
Merged pull requests:
- faster batching (#122) (@CarloLucibello)
- fix GATv2Conv show (#129) (@CarloLucibello)
v0.3.11
GraphNeuralNetworks v0.3.11
Merged pull requests:
- CompatHelper: bump compat for NNlibCUDA to 0.2, (keep existing compat) (#120) (@github-actions[bot])
- implement hash for GNNGraph (#121) (@CarloLucibello)
v0.3.10
GraphNeuralNetworks v0.3.10
Closed issues:
- Implement add_reverse_edges (#103)
- propagate() is 20x slower than built-in sparse matmul (#106)
- add fusing propagate specialization for e_mul_xj (#108)
- implement set_edge_weights (#110)
Merged pull requests:
- fused e_mul_xj and weighted option for adjacency_matrix (#107) (@CarloLucibello)
- Typecast GNNGraph.num_nodes to Int (#109) (@abieler)
- Potential Spelling fix (#111) (@umbriquse)
- add w_mul_xj and set_edge_weight (#114) (@CarloLucibello)
- support for aggregating edge feature in remove_multi_edges (#115) (@CarloLucibello)
- add
to_bidirected
(#116) (@CarloLucibello) - add Google Summer of Code [GSOC] doc page (#117) (@CarloLucibello)
- CompatHelper: bump compat for NNlib to 0.8, (keep existing compat) (#119) (@github-actions[bot])
v0.3.9
GraphNeuralNetworks v0.3.9
Closed issues:
- Problem with InlineStrings.jl (#98)
- Include undirected graphs (#101)
- Merging multiple feature arrays (#102)
- conflict with CSV and GNNGraphs when running Flux.batch (#104)
Merged pull requests:
- workaround for sort ambiguity in cat_features (#105) (@CarloLucibello)
v0.3.8
GraphNeuralNetworks v0.3.8
Closed issues:
- Custom Function GPU Compatibitlity Issue: Indexing (#91)
- Flux.batch Overloading for Generators (#92)
- outputsize for GNNChain (#96)
Merged pull requests:
- add sample_neighbors (#93) (@CarloLucibello)
- CompatHelper: bump compat for LearnBase to 0.6, (keep existing compat) (#95) (@github-actions[bot])
- Adds GATv2 layer (#97) (@abieler)