Aug. 20, 2023, 6:01 a.m. | /u/qalis

Machine Learning www.reddit.com

Hi! I want to share with you my new paper, ["Strengthening structural baselines for graph classification using Local Topological Profile"](https://arxiv.org/abs/2305.00724) (code on [Github](https://github.com/j-adamczyk/LTP/blob/master/main.py)). It was presented during ICCS 2023 conference ([official publication](https://link.springer.com/book/10.1007/978-3-031-36027-5)).

Graph classification is important in social networks analysis, de novo drug design, bioinformatics, materials science etc. A popular tool nowadays are Graph Neural Networks (GNNs), but they are data-hungry and hard to train for graph classification (compared to node classification). They also have problems with using subgraph information, …

analysis bioinformatics classification data design drug design etc gnns graph graph neural networks information machinelearning materials materials science networks neural networks node paper popular science social social networks tool

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