Research|
VaR Estimation with Conditional GANs and GCNs
The problem of Continual Learning has drawn much interest in recent years, as training AI models able to learn new tasks or move to new domains poses the risk of forgetting earlier knowledge. In this study, we have applied several CL methods to train time series forecasting models in the financial domain, using Bayesian changepoint detection methods to segment series into different regimes and thus framing the problem as one of Domain-Incremental Learning. Work presented at Ital-IA 2022.