Abstract: Graph representation learning (GRL) is fundamental in multi-graph applications like molecular property prediction. Graph neural networks (GNNs) have emerged as a popular method for GRL.

We propose a novel deep learning framework, STGCN, to tackle time series prediction problem in traffic domain. Instead of applying regular convolutional and recurrent units, we formulate the problem ...

Autonomous_Quiz_Agent/ ├── README.md ├── notes.txt ├── pytest.ini ├── requirements.txt ├── .env # Backend environment variables (local ...