Abstract: Reliable interval forecasting of uncertain load with cyberattacks is ... model is employed to extract long- and short-term temporal dependencies of load time series. Then, an optimal ...

Pre-trained foundation models are making time-series forecasting more accessible and available, unlocking its benefits for ...

Following polling at the time, we discounted Trump’s re-election ... but a disorderly loss of confidence in Treasuries would be so disastrous for US markets, including stocks, that the comeback ...

Abstract: It represents a meta learning framework for financial time series forecasting that can adapt pretty easily to new financial market datasets with very small retrains. In this methodology, it ...

This caught many by surprise and left some shocked, especially market analysts and economists who make a living by forecasting and ... broader question of the confidence with which such forecasts ...

Confidence votes are rare in Germany, a country of 83 million people that prizes stability. This was only the sixth time in its postwar history that a chancellor had called one. The last was in ...

Event Will Feature Appearances by TIME Athlete of the Year Caitlin Clark, TIME CEO of the Year Lisa Su, TIME Icon of the Year Elton John, and More in New York City New York, NY–December 11 ...