Recency-Weighted Temporally-Segmented Ensemble for Time-Series Modeling

1 code implementation • 4 Mar 2024 • Pål V. Johnsen, Eivind Bøhn, Sølve Eidnes, Filippo Remonato, Signe Riemer-Sørensen

Addressing this, we introduce the Recency-Weighted Temporally-Segmented (ReWTS, pronounced `roots') ensemble model, a novel chunk-based approach for multi-step forecasting.

Time Series

Linear Antisymmetric Recurrent Neural Networks

no code implementations • L4DC 2020 • Signe Moe, Filippo Remonato, Esten Ingar Grøtli, Jan Tommy Gravdahl

Recurrent Neural Networks (RNNs) have a form of memory where the output from a node at one timestep is fed back as input the next timestep in addition to data from the previous layer.