Why Traditional MSE Fails in Time Series Forecasting and How Diffusion Models Fix It
Standard Mean Squared Error metrics often fail in probabilistic time series forecasting because models can match the correct mean and variance while predicting impossible future scenarios. A new approach utilizing a diffusion head resolves this flaw by generating realistic trajectory distributions, significantly improving prediction reliability for complex sequential data.
Source: Towards Data Science