Rethinking the message passing for graph-level classification tasks in a category-based view
Message-Passing Neural Networks (MPNNs) have emerged as a popular framework for graph representation in recent years. However, the graph readout function in MPNNs often leads to significant information loss, resulting in performance degradation and computational waste for graph-level classification...
| Main Authors: | , , , |
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| Other Authors: | |
| Format: | Journal Article |
| Language: | English |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/182539 |