The impact of data set similarity and diversity on transfer learning success in time series forecasting
Pre-trained models have become pivotal in enhancing the efficiency and accuracy of time
series forecasting on target data sets by leveraging transfer learning. While benchmarks …
series forecasting on target data sets by leveraging transfer learning. While benchmarks …
Ensemble Transfer Learning for Time Series Forecasting: a Sensitivity Analysis Framework for a Shallow Neural Network
Transfer learning applied to time-series forecasting is a current topic of high interest to the
machine learning community. This paper addresses the need for empirical studies, as …
machine learning community. This paper addresses the need for empirical studies, as …
Transformers in Time Series Forecasting: A Brief Transfer Learning Performance Analysis
WV Kambale, DK Kadurha… - … on Circuits, Systems …, 2023 - ieeexplore.ieee.org
Transformer models have risen to the challenge of delivering high prediction capacity for
long-term time-series forecasting. Several transformer architectures designed for time series …
long-term time-series forecasting. Several transformer architectures designed for time series …
A Boxplot Metadata Configuration Impact on Time Series Forecasting and Transfer Learning
The potential impact of metadata on enhancing the accuracy and reliability of time series
forecasting is increasingly being recognized. Including metadata in forecasting models …
forecasting is increasingly being recognized. Including metadata in forecasting models …