Temporal Empirical Dynamic Modeling

Researching causal relationships in time series data using Temporal Convolutional Networks (TCNs) combined with attention mechanisms. This approach aims to identify complex temporal interactions. Additionally, we're incorporating uncertainty quantification to enhance the reliability of our causal predictions.

Temporal Causal Discovery from Autocorrelated and Non-Stationary Time Series Data