Benchmarking Graph Transformers Toward Scalability for Large Graphs
Graph transformers (GTs) have gained popularity as an alternative to graph neural networks (GNNs) for deep learning on graph-structured data. In particular, the self-attention mechanism of GTs mitigates the fundamental limitations of over-squashing, over-smoothing, and limited expressiveness that GN...
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| Format: | Thesis |
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Massachusetts Institute of Technology
2024
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| Online Access: | https://hdl.handle.net/1721.1/156988 |