GraphNeuralNetworks-v0.6.23

GraphNeuralNetworks GraphNeuralNetworks-v0.6.23

Diff since GraphNeuralNetworks-v0.6.22

Merged pull requests:

• improve GNNLux docs (#542) (@CarloLucibello)
• Add version selector (#543) (@aurorarossi)
• Add Hands On tutorial GNNLux (#549) (@aurorarossi)
• try new approach for building and deploying docs (#552) (@CarloLucibello)

Closed issues:

• Stack Layers in a HeteroGraphConv Model (#541)
• [lux] add tutorials (#544)

GNNlib-v0.2.5

GNNlib GNNlib-v0.2.5

GNNlib-v0.2.4

GNNlib GNNlib-v0.2.4

GNNLux-v0.1.1

GNNLux GNNLux-v0.1.1

Diff since GNNLux-v0.1.0

Merged pull requests:

• docs improvements (#539) (@CarloLucibello)
• improve GNNLux docs (#542) (@CarloLucibello)
• Add version selector (#543) (@aurorarossi)
• Add Hands On tutorial GNNLux (#549) (@aurorarossi)
• try new approach for building and deploying docs (#552) (@CarloLucibello)

Closed issues:

• [docs] move tutorials to GraphNeuralNetworks.jl package (#533)
• Stack Layers in a HeteroGraphConv Model (#541)
• [lux] add tutorials (#544)

GNNGraphs-v1.3.1

GNNGraphs GNNGraphs-v1.3.1

Diff since GNNGraphs-v1.3.0

Merged pull requests:

• simplify documentation (#531) (@CarloLucibello)
• Add token to codecov action (#532) (@gdalle)
• revisit docs organization (#535) (@CarloLucibello)
• docs improvements (#539) (@CarloLucibello)
• updates to GNNLux for first release (#540) (@CarloLucibello)
• improve GNNLux docs (#542) (@CarloLucibello)
• Add version selector (#543) (@aurorarossi)
• Add Hands On tutorial GNNLux (#549) (@aurorarossi)
• try new approach for building and deploying docs (#552) (@CarloLucibello)

Closed issues:

• coverage not displayed in readme (#528)
• [docs] move tutorials to GraphNeuralNetworks.jl package (#533)
• Stack Layers in a HeteroGraphConv Model (#541)
• [lux] add tutorials (#544)

GraphNeuralNetworks-v0.6.22

GraphNeuralNetworks GraphNeuralNetworks-v0.6.22

Merged pull requests:

• Coloring refinement algorithm (#444) (@CarloLucibello)
• separate GNNGraphs from GNNlib (#446) (@CarloLucibello)
• Add possibility to pass weights to GCNConv (#447) (@aurorarossi)
• Add DCGRU temporal layer (#448) (@aurorarossi)
• temporarily reintegrate GNNGraphs tests (#449) (@CarloLucibello)
• CI for GNNGraphs.jl (#451) (@CarloLucibello)
• make GraphNeuralNetworks.jl depend on GNNGraphs.jl (#453) (@CarloLucibello)
• drop_nodes -> remove_nodes (#454) (@CarloLucibello)
• fix docs (#455) (@CarloLucibello)
• move mldatasets2gnngraph (#458) (@CarloLucibello)
• create GNNLux.jl package (#460) (@CarloLucibello)
• [GNNLux] GCNConv, ChebConv, GNNChain (#462) (@CarloLucibello)
• [GNNLux] more layers (#463) (@CarloLucibello)
• use GNNlib in GNN.jl (#464) (@CarloLucibello)
• [GNNlib] fix cuda ext (#465) (@CarloLucibello)
• tests for GNNlib (#466) (@CarloLucibello)
• fix docs (#467) (@CarloLucibello)
• [GNNLux] fix tests (#468) (@CarloLucibello)
• [GNNLux] more layers (#469) (@CarloLucibello)
• [GNNLux] TGCN temporal layer (#470) (@aurorarossi)
• [GNNLux] more layers pt. 3 (#471) (@CarloLucibello)
• [GNNGraphs] implement remove_edges(g, p) (#474) (@rbSparky)
• [GNNLux] Added SGConv (#475) (@rbSparky)
• fix dense test (#479) (@CarloLucibello)
• [GNNLux] Adding MegNetConv Layer (#480) (@rbSparky)
• rng instead of seed for rand_graph (#482) (@CarloLucibello)
• @functor ->@layer (#484) (@CarloLucibello)
• [GNNLux] Add A3TGCN temporal layer (#485) (@aurorarossi)
• [GNNLux] Add GConvLSTM, GConvGRU and DCGRU temporal layers (#487) (@aurorarossi)
• fix NNConv docs (#488) (@CarloLucibello)
• Add EvolveGCNO temporal layer (#489) (@aurorarossi)
• [GNNLux] updates for Lux v1.0 (#490) (@CarloLucibello)
• [GNNLux] Adding NNConv Layer (#491) (@rbSparky)
• [GNNLux] add GMMConv, ResGatedGraphConv (#494) (@CarloLucibello)
• move GraphNeuralNetworks to a single folder (#496) (@CarloLucibello)
• feat: add NeighborLoader (#497) (@askorupka)
• feat: add induced_subgraph functionality (#499) (@askorupka)
• [GNNLux] Adding SAGEConv Layer (#500) (@rbSparky)
• fix vector DataStore (#505) (@CarloLucibello)
• Documentation with MultiDocumenter.jl (#508) (@aurorarossi)
• Fix badge link (#509) (@aurorarossi)
• Passing multidocs workflows in PRs (#510) (@aurorarossi)
• [Docs] New introduction to monorepo (#512) (@aurorarossi)
• GNNLux docs start and general docs improvement (#513) (@aurorarossi)
• Add GNNLux docstrings (#515) (@aurorarossi)
• Add GNNLux temporal convolutional layers docstrings and docs (#516) (@aurorarossi)
• move GraphNeuralNetworks.jl to TestItems.jl (#517) (@CarloLucibello)
• more updates for the tests (#519) (@CarloLucibello)
• Remove preview docs (#520) (@aurorarossi)
• Add GNNLux training example in docs (#521) (@aurorarossi)
• Move NeighborLoader to GNNGraphs (#522) (@aurorarossi)
• Bump codecov/codecov-action from 4 to 5 (#525) (@dependabot[bot])
• add buildkite workflow (#526) (@CarloLucibello)
• buildkite AMDGPU (#529) (@CarloLucibello)
• buildkite for GNNlib + get_graph_type (#530) (@CarloLucibello)
• simplify documentation (#531) (@CarloLucibello)
• Add token to codecov action (#532) (@gdalle)
• revisit docs organization (#535) (@CarloLucibello)
• docs improvements (#539) (@CarloLucibello)
• updates to GNNLux for first release (#540) (@CarloLucibello)

Closed issues:

• plan for splitting the package (#450)
• use Flux.@layer instead of Flux.@functor (#452)
• consider using MultiDocumenter (#456)
• reinstate temporal graphs tutorials (#457)
• random graph generators should take an rng instead of a seed (#459)
• plan for GNNLux.jl (#461)
• Cannot create GNNGraph with unconnected nodes (#472)
• Implementation of recommender system based on GNN (#473)
• GNNs.jl's CI is failing for GRAPH_T = :dense (#476)
• move all tests to TestItems.jl and TestItemsRunner.jl (#477)
• document the monorepo structure and the package dependencies (#483)
• GCNConv layer fails when the GNNGraph comes from an adjacency matrix (#486)
• move GraphNeuralNetworks.jl to its own folder (#495)
• Comparison to GeometricFlux.jl (#502)
• Overriding Base.getproperty(vds::Vector{DataStore}, s::Symbol) conflicts A.ref usage in julia (#504)
• move repo to JuliaGraphs org (#506)
• move NeighborLoader to GNNGraphs (#507)
• coverage not displayed in readme (#528)
• [docs] move tutorials to GraphNeuralNetworks.jl package (#533)

GNNLux-v0.1.0

GNNLux GNNLux-v0.1.0

Initial release.

GNNGraphs-v1.3.0

GNNGraphs GNNGraphs-v1.3.0

Merged pull requests:

• move GraphNeuralNetworks to a single folder (#496) (@CarloLucibello)
• feat: add NeighborLoader (#497) (@askorupka)
• feat: add induced_subgraph functionality (#499) (@askorupka)
• [GNNLux] Adding SAGEConv Layer (#500) (@rbSparky)
• fix vector DataStore (#505) (@CarloLucibello)
• Documentation with MultiDocumenter.jl (#508) (@aurorarossi)
• Fix badge link (#509) (@aurorarossi)
• Passing multidocs workflows in PRs (#510) (@aurorarossi)
• [Docs] New introduction to monorepo (#512) (@aurorarossi)
• GNNLux docs start and general docs improvement (#513) (@aurorarossi)
• Add GNNLux docstrings (#515) (@aurorarossi)
• Add GNNLux temporal convolutional layers docstrings and docs (#516) (@aurorarossi)
• move GraphNeuralNetworks.jl to TestItems.jl (#517) (@CarloLucibello)
• more updates for the tests (#519) (@CarloLucibello)
• Remove preview docs (#520) (@aurorarossi)
• Add GNNLux training example in docs (#521) (@aurorarossi)
• Move NeighborLoader to GNNGraphs (#522) (@aurorarossi)
• Bump codecov/codecov-action from 4 to 5 (#525) (@dependabot[bot])
• add buildkite workflow (#526) (@CarloLucibello)
• buildkite AMDGPU (#529) (@CarloLucibello)
• buildkite for GNNlib + get_graph_type (#530) (@CarloLucibello)

Closed issues:

• Differences to GeometricFlux.jl? (#2)
• add benchmarks (#4)
• register package (#5)
• add documentation (#6)
• add examples (#7)
• implement graph concatenation (#12)
• improve documentation (#14)
• pretty print GNNGraph (#23)
• define a message_and_aggregate method (#29)
• index not displayed in documentation pages (#32)
• A Logo is needed (#35)
• add support to edge weight in GCNConv (#40)
• TagBot trigger issue (#44)
• Problem with GNNChain and NNConv (#49)
• graph NeuralODE example not working on gpu (#56)
• Adding a GATv2 layer (#74)
• Move the package to the FluxML org (#80)
• Explainer vs GeometricFlux (#81)
• Weights not included in GNNGraph made from SimpleWeightedDiGraph (#85)
• Hash function for GNNGraph (#87)
• no method matching getobs(::NamedTuple{(:x,), Tuple{Matrix{Float32}}} (#88)
• Custom Function GPU Compatibitlity Issue: Indexing (#91)
• Flux.batch Overloading for Generators (#92)
• outputsize for GNNChain (#96)
• Problem with InlineStrings.jl (#98)
• batching scales quadratically (#99)
• Include undirected graphs (#101)
• Merging multiple feature arrays (#102)
• Implement add_reverse_edges (#103)
• conflict with CSV and GNNGraphs when running Flux.batch (#104)
• propagate() is 20x slower than built-in sparse matmul (#106)
• add fusing propagate specialization for e_mul_xj (#108)
• implement set_edge_weights (#110)
• Question about temporal graph neural networks (#112)
• Gradient of edge weights is nothing with fused e_mul_xj (#113)
• aggregate_neighbors() is 100x slower than equivalent sparse matrix operation (#124)
• Failure to combine SparseDiffTools.autoback_hesvec and GCNConv (#125)
• GATv2Conv show method errors (#126)
• Support edge attributes in as many layers as possible (#128)
• 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)
• Heterogeneous graphs support (#144)
• hope can load dataset with GraphMLDatasets.jl (#149)
• GPU memory filling up (#150)
• Citing GraphNeuralNetworks.jl (#151)
• GSoC 2022 (#157)
• Open Graph Benchmark integration (#162)
• message passing for multiple feature arrays (#166)
• Construct Graphs.SimpleDiGraph graphs from GNNGraphs (#167)
• Add tutorials written in Pluto (#168)
• Info about features in the compact show (#169)
• don't automatically batch when getobs from an array of graphs (#170)
• Inaccurate GATv2Conv Documentation (#175)
• add radius_graph api (#177)
• add show methods for WithGraph and GNNChain (#178)
• knn_graph yields same results with or without self loops (#179)
• Missing bounds checking when working on GPU (#181)
• Spelling Error of edge? (#184)
• Duplicate indexes in documents (#187)
• Implement GraphWorld for fake graphs benchmarking (#188)
• Implement Learnable Structural Positional Encoding (LSPE) (#190)
• copy(::GNNGraph)? (#191)
• Some design issues (#193)
• Support for Heterogeneous Graphs (#199)
• Flux destructure/restructure bug (#200)
• Remove hard dependency on GraphNeuralNetworks from Pluto Notebooks (#204)
• NNConv tests are failing (#208)
• Allow for additonal features in GNNGraph (#210)
• Question about the GCNConv layer code (#211)
• Support for multiple graphs in GNNGraph (#212)
• Formatting errors in the tutorial (#213)
• Generation of documentation is very slow because of Pluto (#227)
• GNN.jl in tutorials (#228)
• Julia Formatter (#238)
• GNNGraph with multiple edge features not working (#243)
• Overflows in GATConv and GATv2Conv (#246)
• Convolutions for GNNHeteroGraphs (#254)
• Update documentation: Convolutional Layers (#255)
• Dropout inside GATConv layer (#258)
• Bad performance of GCNConv (#259)
• Documentation link (#262)
• GCNConv without normalization (#277)
• add_edges adds a non-existent edge to its DataStore (#280)
• Graph classification: multiple graphs associated with a common label (#282)
• need more informative error for dimension mismatch (#283)
• convenience feature setter (#284)
• @functor default for GNNLayers (#288)
• add docs for HeteroGraphConv (#302)
• add batching for GNNHeteroGraph (#303)
• Local pooling in graph regression/classification problems (#307)
• use extension instead of CUDA hard dependence (#317)
• Update Flux.trainable (#323)
• AGNNConv behaviour different from mathematical definition (due to self loops) (#325)
• implement add_self_loops(g, edge_t) for heterographs (#329)
• Edge weights not properly documented for GNNHeteroGraphs (and implement new function to add new edge weights?) (#331)
• HeteroGraphConv bug: ERROR: duplicate field name in NamedTuple: "movie" is not unique (#332)
• add_edges for GNNHeteroGraph does not allow providing the number of nodes (#334)
• add empty constructor for heterograph (#338)
• The constraint in Flux.batch(gs::AbstractVector{<:GNNHeteroGraph}) does not seem to be strong enough (#341)
• Error in Example Code (#346)
• Outdated default package installation (#348)
• View arrays on GPU cause scalar indexing error (#349)
• documentation proposal (#357)
• support Lux (#372)
• getgraph not working on GPU (#377)
• Example given for GNNGraph results in error (#380)
• Error in one of the examples in the Working with GNNGraph page (#401)
• Duplicated method definitions of GINConv (#406)
• turn this into a monorepo (#433)
• Maybe state difference with GeometricFlux.jl. (#435)
• plan for splitting the package (#450)
• use Flux.@layer instead of Flux.@functor (#452)
• consider using MultiDocumenter (#456)
• reinstate temporal graphs tutorials (#457)
• random graph generators should take an rng instead of a seed (#459)
• plan for GNNLux.jl (#461)
• Cannot create GNNGraph with unconnected nodes (#472)
• Implementation of recommender system based on GNN (#473)
• GNNs.jl's CI is failing for GRAPH_T = :dense (#476)
• move all tests to TestItems.jl and TestItemsRunner.jl (#477)
• document the monorepo structure and the package dependencies (#483)
• GCNConv layer fails when the GNNGraph comes from an adjacency matrix (#486)
• move GraphNeuralNetworks.jl to its own folder (#495)
• Comparison to GeometricFlux.jl (#502)
• Overriding Base.getproperty(vds::Vector{DataStore}, s::Symbol) conflicts A.ref usage in julia (#504)
• move repo to JuliaGraphs org (#506)
• move NeighborLoader to GNNGraphs (#507)

v0.6.21

GraphNeuralNetworks v0.6.21

Diff since v0.6.20

Merged pull requests:

• Add DCGRU temporal layer (#448) (@aurorarossi)
• move mldatasets2gnngraph (#458) (@CarloLucibello)
• create GNNLux.jl package (#460) (@CarloLucibello)
• [GNNLux] GCNConv, ChebConv, GNNChain (#462) (@CarloLucibello)
• [GNNLux] more layers (#463) (@CarloLucibello)
• use GNNlib in GNN.jl (#464) (@CarloLucibello)
• [GNNlib] fix cuda ext (#465) (@CarloLucibello)
• tests for GNNlib (#466) (@CarloLucibello)
• fix docs (#467) (@CarloLucibello)
• [GNNLux] fix tests (#468) (@CarloLucibello)
• [GNNLux] more layers (#469) (@CarloLucibello)
• [GNNLux] TGCN temporal layer (#470) (@aurorarossi)
• [GNNLux] more layers pt. 3 (#471) (@CarloLucibello)
• [GNNGraphs] implement remove_edges(g, p) (#474) (@rbSparky)
• [GNNLux] Added SGConv (#475) (@rbSparky)
• fix dense test (#479) (@CarloLucibello)
• [GNNLux] Adding MegNetConv Layer (#480) (@rbSparky)
• rng instead of seed for rand_graph (#482) (@CarloLucibello)
• @functor ->@layer (#484) (@CarloLucibello)
• [GNNLux] Add A3TGCN temporal layer (#485) (@aurorarossi)
• [GNNLux] Add GConvLSTM, GConvGRU and DCGRU temporal layers (#487) (@aurorarossi)
• fix NNConv docs (#488) (@CarloLucibello)
• Add EvolveGCNO temporal layer (#489) (@aurorarossi)
• [GNNLux] updates for Lux v1.0 (#490) (@CarloLucibello)
• [GNNLux] Adding NNConv Layer (#491) (@rbSparky)
• [GNNLux] add GMMConv, ResGatedGraphConv (#494) (@CarloLucibello)

Closed issues:

• Question about temporal graph neural networks (#112)
• add show methods for WithGraph and GNNChain (#178)
• Dropout inside GATConv layer (#258)
• Graph classification: multiple graphs associated with a common label (#282)
• convenience feature setter (#284)
• @functor default for GNNLayers (#288)
• documentation proposal (#357)
• support Lux (#372)
• turn this into a monorepo (#433)
• use Flux.@layer instead of Flux.@functor (#452)
• random graph generators should take an rng instead of a seed (#459)
• Cannot create GNNGraph with unconnected nodes (#472)
• Implementation of recommender system based on GNN (#473)
• GNNs.jl's CI is failing for GRAPH_T = :dense (#476)
• GCNConv layer fails when the GNNGraph comes from an adjacency matrix (#486)

v0.6.20

GraphNeuralNetworks v0.6.20

Diff since v0.6.19

Merged pull requests:

• Added perturb_edges function (#423) (@rbSparky)
• Add drop_nodes transform (#426) (@rbSparky)
• Added Personalized PageRank Diffusion [ppr_diffusion function] (#427) (@rbSparky)
• Added TAGConv layer (#430) (@rbSparky)
• create GNNlib.jl (#432) (@CarloLucibello)
• Create Register.yml (#434) (@CarloLucibello)
• Add GConvLSTM temporal layer (#437) (@aurorarossi)
• Add GConvGRU temporal layer (#438) (@aurorarossi)
• Add DConv layer (#441) (@aurorarossi)
• CompatHelper: bump compat for KrylovKit to 0.8, (keep existing compat) (#442) (@github-actions[bot])
• Coloring refinement algorithm (#444) (@CarloLucibello)
• separate GNNGraphs from GNNlib (#446) (@CarloLucibello)
• Add possibility to pass weights to GCNConv (#447) (@aurorarossi)
• temporarily reintegrate GNNGraphs tests (#449) (@CarloLucibello)
• CI for GNNGraphs.jl (#451) (@CarloLucibello)
• make GraphNeuralNetworks.jl depend on GNNGraphs.jl (#453) (@CarloLucibello)
• drop_nodes -> remove_nodes (#454) (@CarloLucibello)
• fix docs (#455) (@CarloLucibello)

Closed issues:

• Maybe state difference with GeometricFlux.jl. (#435)