How to handle temporal dimension with Graph Neural Networks
I’ve just starting using PyTorch Geometric, and for my problem I have batched data with a time dimension. My tensor has shape [batch, seq_len, nodes, features].
How to handle temporal dimmension with Graph Neural Networks
I’ve just starting using PyTorch Geometric, and for my problem I have batched data with a time dimmension. My tensor has shape [batch, seq_len, nodes, features] . I want to apply the GCNConv layer separatly to each seq_len step, but the GCNConv layer expects a input of [Nodes, Features], as states in the docs.