Feb 11, 2024 · Probabilistic Time Series Forecasting ... In univariate time series modelling the dataset comprises of one or more time series, each sampled at ...

These models can produce multi-step ahead forecasts using multivariate time series as inputs. The application of these models was demonstrated in the context of ...

Feb 1, 2023 · Our studies discover a new attack pattern that negatively impact the forecasting of a target time series via making strategic, sparse ( ...

This approach improves robustness and alleviates overfitting compared to standard methods. In addition, to improve the accuracy of model forecasts on severely ...

Probabilistic time series forecasting has played critical role in decision-making processes due to its capability to quantify uncertainties. 33. 24 Feb 2022.

Apr 1, 2022 · Time series forecasting aims to estimate probability distribution based on given time series observation values at future time points. It is a ...

This work studies the threats of adversarial attack on multivariate probabilistic forecasting models and viable defense mechanisms.

Mar 5, 2024 · Existing state-of-the-art robust forecasting models decompose time series into independent functions covering trends and periodicities. However, ...

Robustness characteristics based on the mean square risk of forecasting are introduced and evaluated for these cases. In addition, new robust forecasting ...

Jun 16, 2022 · Probabilistic hierarchical time-series forecasting is an important variant of time-series forecasting, where the goal is to model and ...