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@youph youph released this Oct 25, 2019 · 46 commits to develop since this release

We are excited to announce the 0.8.0 release of the library. This release extends stellargraph by adding new algorithms and demos, enhancing interpretability via saliency maps for GAT, and further simplifying graph ML workflows through standardised model APIs and arguments. More details on new features and enhancements are listed below.

New algorithms:

  • Directed GraphSAGE algorithm (a generalisation of GraphSAGE to directed graphs) + demo #479
  • Attri2vec algorithm + demo #470 #455
  • PPNP and APPNP algorithms + demos #485
  • GAT saliency maps for interpreting node classification with Graph Attention Networks + demo #435

Implemented enhancements:

  • New demo of node classification on Twitter hateful users \430
  • New demo of graph saliency on Twitter hateful users #448
  • Added Directed SampledBFS walks on directed graphs #464
  • Unified API of GCN, GAT, GraphSAGE, and HinSAGE classses by adding build() method to GCN and GAT classes #439
  • Added activations argument to GraphSAGE and HinSAGE classes #381
  • Unified activations for GraphSAGE, HinSAGE, GCN and GAT #493 #381
  • Added optional regularisation on the weights for GCN, GraphSage, and HinSage #172 #469
  • Unified regularisation of GraphSAGE, HinSAGE, GCN and GAT #494 (geoffj-d61)
  • Unsupervised GraphSage speed up via multithreading #474 #477
  • Support of sparse generators in the GCN saliency map implementation. #432


  • Refactored Ensemble class into Ensemble and BaggingEnsemble. The former implements naive ensembles and the latter bagging ensembles. #459
  • Changed from using keras to use tensorflow.keras #471
  • Removed flatten_output arguments for all models #447

Fixed bugs:

  • Updated Yelp example to support new dataset version #442
  • Fixed bug where some nodes and edges did not get a default type #451
  • Inconsistency in Ensemble.fit_generator() argument #461
  • Fixed source--target node designations for code using Cora dataset #444
  • IndexError: index 1 is out of bounds for axis 1 with size 1 in: demos/node-classification/hinsage #434
  • GraphSAGE and GAT/GCN predictions have different shapes #425
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