Added Total Influence - Measuring Long-range Dependency in GNN #10263
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May 11, 2025 03:32
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Dear PyG Team, Following the previous PR [[#10263]](#10263) on the long-range measurement, we slightly modified the text description of the method and added a link to our paper. Sorry for the extra changes and thanks in advance for the quick review! Huidong --------- Co-authored-by: Leon <huidongl@omi-rapid-17.omirapid.oxford-man.ox.ac.uk> Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> Co-authored-by: Matthias Fey <matthias.fey@tu-dortmund.de> Co-authored-by: Leon <huidongl@omi-rapid-14.omirapid.oxford-man.ox.ac.uk>
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Dear PyG Team,
Thank you for your effort in supporting our graph learning community!
This is Huidong from the Machine Learning Research Group at University of Oxford. As a follow-up to our recent PR[#10115] of the CityNetwork dataset, we now release Total Influence, a measurement introduced in our paper which quantifies the long-range dependency in GNNs. Additionally, we also fixed some typos and slightly modified the comment description of CityNetwork in this current PR.
Please let me know if you need further information from me. Thanks again for helping us with our work!
Huidong Liang
PhD Student @ MLRG
Department of Engineering Science
Univeristy of Oxford