Update documentation and examples README

snap-stanford · Apr 4, 2021 · 652734c · 652734c
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diff --git a/docs/source/notes/other.rst b/docs/source/notes/other.rst
@@ -4,4 +4,5 @@ Other Resources
 * **PyTorch Geometric** - PyTorch Geometric is a geometric deep learning extension library for `PyTorch <https://pytorch.org/>`_ [`Paper <https://arxiv.org/abs/1903.02428>`__, `GitHub <https://github.com/rusty1s/pytorch_geometric>`__, `Documentation <https://pytorch-geometric.readthedocs.io/en/latest/index.html>`__]
 * **SNAP** - A general purpose network analysis and graph mining library [`Paper <https://arxiv.org/abs/1606.07550>`__, `GitHub <https://github.com/snap-stanford/snap-python>`__, `Documentation <https://snap.stanford.edu/snappy/doc/index.html>`__]
 * **NetworkX** - A Python package for the creation, manipulation, and study of the structure, dynamics, and functions of complex networks [`Paper <http://conference.scipy.org/proceedings/SciPy2008/paper_2/>`__, `GitHub <https://github.com/networkx/networkx>`__, `Documentation <https://networkx.org/>`__]
-* **CS224W** - Stanford Machine Learning with Graphs (Winter 2021) [`Website <http://web.stanford.edu/class/cs224w/>`__]
+* **CS224W** - Stanford Machine Learning with Graphs (Winter 2021) [`Website <http://web.stanford.edu/class/cs224w/>`__]
+* **GraphGym** - GraphGym is a platform for designing and evaluating Graph Neural Networks (GNNs) [`Paper <https://arxiv.org/abs/2011.08843>`__, `GitHub <https://github.com/snap-stanford/GraphGym>`__]
diff --git a/examples/graph_classification/README.md b/examples/graph_classification/README.md
@@ -2,7 +2,7 @@
 
 * [Graph classification on TU (graph backend)](graph_classification_TU.py): Graph classification on the TU dataset graphs using the NetworkX as the DeepSNAP graph manipulation backend.
 * [Graph classification on TU (tensor backend)](graph_classification_TU_tensor.py): Graph classification on the TU dataset graphs only using tensors as the DeepSNAP graph manipulation backend.
-* [Graph classification on TU (transformation)](graph_classification_TU_transform.py): Graph classification on the TU dataset graphs with transformations.
+* [Graph classification on TU (transformation)](graph_classification_TU_transform.py): Graph classification on the TU dataset graphs with transformations. For more graph classification with transformation examples, please see the [GraphGym](https://github.com/snap-stanford/GraphGym).
 
 ## Training