Xavier Bresson: New paper on benchmarking graph neural networks w/ @vijaypradwi @chaitjo T. Laurent and Y. Bengio
Our goal was to identify trends and good building blocks for GNNs. https://t.co/PiFUYm5Z3R
8 replies, 501 likes
Chaitanya Joshi: **Benchmarking Graph Neural Networks**!
Fortunate to have been part of this effort, with @vijaypradwi, @xbresson, Thomas Laurent (LMU), & Yoshua Bengio (@MILAMontreal).
#GraphNeuralNetworks #DeepLearning https://t.co/5JdGjzTIU5
4 replies, 180 likes
Xavier Bresson: Excited to release a major update of our project "Benchmarking Graph Neural Networks"
1 replies, 180 likes
Yann LeCun: Graph neural net benchmarks with repo.
0 replies, 163 likes
Thomas Kipf: Exciting new work on benchmarks for graph neural nets
0 replies, 104 likes
DeepGraphLibrary: Awesome new benchmarks for GNNs by NTU Graph Deep Learning Lab!! Datasets from computer vision, bioinformatics to combinatorial optimization. A great test field for new models. Powered by DGL!
0 replies, 71 likes
Chaitanya Joshi: @huggingface @slashML Also, for those new to Graph Deep Learning/GNNs, you'll find our new paper useful for building intuitions.
1 replies, 14 likes
Vijay Dwivedi: Paper on 'Benchmarking Graph Neural Networks' with @chaitjo, @xbresson, Thomas Laurent, and Yoshua Bengio released now.
1 replies, 12 likes
elvis: This is so cool! If you are into GNNs, here is the provided framework for benchmarking GNNs -- it's aimed at reproducibility.
0 replies, 5 likes
Simone Scardapane: @paolo_galeone @A_K_Nain Random suggestions below. :-) 3/x
5. Recent benchmarks highlighting some challenges: https://arxiv.org/pdf/2003.00982.pdf or https://arxiv.org/abs/1912.09893
6. If you are interested in theory (e.g., expressivity): https://arxiv.org/abs/1810.00826
7. Definitely check out videos here: https://geometric-relational-dl.github.io/
1 replies, 4 likes
Found on Mar 03 2020 at https://arxiv.org/pdf/2003.00982.pdf