D. van den Poel

TMAML: Temporal Model-Agnostic Meta-Learning for Cold-Start Time Series Forecasting

Cold-start forecasting, the task of forecasting a time series with little to no historical data, is a common challenge. Addressing it requires approaches that learn quickly from few datapoints and leverage information from related series, typically through static covariates, to generalize well to unseen series. While s...