In complex high-dimensional systems like power grids or COVID-19 transmission, both causal dependencies and temporal information of key variables are essential for dissecting the underlying mechanisms governing system dynamics. This paper presents Causal-oriented Representation Learning Predictor, a neural network framework designed to jointly conduct causal analysis and multistep forecasting.
- Sihua Cai
- Hao Peng
- Pei Chen
