Probabilistic Decomposition Transformer for Time Series Forecasting

Understand

Time series forecasting is crucial for many fields, such as disaster warning, weather prediction, and energy consumption.

• The Transformer-based models are considered to have revolutionized the field of sequence modeling.
• However, the complex temporal patterns of the time series hinder the model from mining reliable temporal dependencies.
• Furthermore, the autoregressive form of the Transformer introduces cumulative errors in the inference step.