Abstract: Long-term Time Series Forecasting (LTSF) aims to predict time series data over extended future horizons. In recent years, multi-scale mixing and multi-period analysis have gained significant ...

An advanced Deep Learning pipeline for spatio-temporal wind speed forecasting using ConvLSTM, PredRNN, and a state-of-the-art Transformer model (PredFormer Fac-T-S). This project handles the entire ...

Abstract: This paper introduces a new hybrid time series forecasting technique to obtain an efficient and accurate daily crude oil prices forecast. The proposed hybrid technique combines the features ...

In the run-up to the winter storm currently pummeling much of the U.S., weather forecasts for some regions were all over the map, with snowfall predictions varying wildly. Nvidia couldn’t have timed ...

Real-world time series often exhibit a non-stationary nature, degrading the performance of pre-trained forecasting models. Test-Time Adaptation (TTA) addresses this by adjusting models during ...