DropGNN: Random Dropouts Increase the Expressiveness of Graph Neural Networks
–Neural Information Processing Systems
Then, we combine the results of these runs to obtain the final result. We prove that DropGNNs can distinguish various graph neighborhoods that cannot be separated by message passing GNNs.
Neural Information Processing Systems
Aug-17-2025, 01:52:33 GMT
- Country:
- Africa > Ethiopia
- Addis Ababa > Addis Ababa (0.04)
- Europe
- North America > Canada
- Alberta > Census Division No. 15
- Improvement District No. 9 > Banff (0.04)
- British Columbia > Vancouver (0.04)
- Alberta > Census Division No. 15
- Oceania > Australia
- New South Wales > Sydney (0.04)
- Africa > Ethiopia
- Genre:
- Overview (0.46)
- Research Report (0.46)
- Technology: