Our key findings:
- Graph ML models can be generalizable yet powerful at the same time
- We offer insights to enhance a model's generalization pre-training
- Findings extend to non-graph ML models as well
24.04.2025 00:06
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Could you please add me? Thx
23.04.2025 14:01
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our paper, “Towards Bridging Generalization and Expressivity of Graph Neural Networks”, will be presented at ICLR 2025 in Singapore this week!
We delve into the connection between expressiveness and generalization of GNNs
🗓 Friday, 25 April
🕙 10:00 am – 12:30 pm SGT
🏢 Hall 3 + Hall 2B
#iclr2025
23.04.2025 03:58
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