2021

Do We Really Need Deep Learning Models for Time Series Forecasting?

Elsayed, Shereen, Thyssens, Daniela, Rashed, Ahmed et al.

Understand

Time series forecasting is a crucial task in machine learning, as it has a wide range of applications including but not limited to forecasting electricity consumption, traffic, and air quality.

Traditional forecasting models rely on rolling averages, vector auto-regression and auto-regressive integrated moving averages.
On the other hand, deep learning and matrix factorization models have been recently proposed to tackle the same problem with more competitive performance.
However, one major drawback of such models is that they tend to be overly complex in comparison to traditional techniques.

Built on

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