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Benchmarking Graph Neural Networks

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Xavier Bresson: New paper on benchmarking graph neural networks w/ @vijaypradwi @chaitjo T. Laurent and Y. Bengio https://arxiv.org/pdf/2003.00982.pdf 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). PDF: https://arxiv.org/pdf/2003.00982.pdf Code: https://github.com/graphdeeplearning/benchmarking-gnns #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" Paper: https://arxiv.org/pdf/2003.00982v2.pdf GitHub: https://github.com/graphdeeplearning/benchmarking-gnns 1/

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. https://twitter.com/chaitjo/status/1234739917583814656?s=20

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. https://github.com/graphdeeplearning/benchmarking-gnns

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


Content

Found on Mar 03 2020 at https://arxiv.org/pdf/2003.00982.pdf

PDF content of a computer science paper: Benchmarking Graph Neural Networks