Projects per year
Abstract
Random walk kernels have been introduced in seminal work on graph learning and were later largely superseded by kernels based on the Weisfeiler-Leman test for graph isomorphism. We give a unified view on both classes of graph kernels. We study walk-based node refinement methods and formally relate them to several widely-used techniques, including Morgan's algorithm for molecule canonization and the Weisfeiler-Leman test. We define corresponding walk-based kernels on nodes that allow fine-grained parameterized neighborhood comparison, reach Weisfeiler-Leman expressiveness, and are computed using the kernel trick. From this we show that classical random walk kernels with only minor modifications regarding definition and computation are as expressive as the widely-used Weisfeiler-Leman subtree kernel but support non-strict neighborhood comparison. We verify experimentally that walk-based kernels reach or even surpass the accuracy of Weisfeiler-Leman kernels in real-world classification tasks.
Original language | English |
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DOIs | |
Publication status | Published - 28 Nov 2022 |
Event | Thirty-sixth Conference on Neural Information Processing Systems: Neurips 2022 - New Orleans Convention Center (hybrid), New Orleans, United States Duration: 28 Nov 2022 → 9 Dec 2022 https://nips.cc/ |
Conference
Conference | Thirty-sixth Conference on Neural Information Processing Systems |
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Country/Territory | United States |
City | New Orleans |
Period | 28/11/22 → 9/12/22 |
Internet address |
Austrian Fields of Science 2012
- 102019 Machine learning
Projects
- 1 Active
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Algorithmic Data Science for Computational Drug Discovery
1/05/20 → 30/11/28
Project: Research funding
Activities
- 1 Poster presentation
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Weisfeiler and Leman Go Walking: Random Walk Kernels Revisited
Nils Morten Kriege (Speaker)
22 Nov 2022 → 9 Dec 2022Activity: Talks and presentations › Poster presentation › Science to Science
Research output
- 1 Preprint
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Weisfeiler and Leman Go Walking: Random Walk Kernels Revisited
Kriege, N. M., 22 May 2022, arXiv.org.Publications: Working paper › Preprint