Comparison of Uncertainty Quantification with Deep Learning in Time Series Regression

Understand

Increasingly high-stakes decisions are made using neural networks in order to make predictions.

• Specifically, meteorologists and hedge funds apply these techniques to time series data.
• When it comes to prediction, there are certain limitations for machine learning models (such as lack of expressiveness, vulnerability of domain shifts and overconfidence) which can be solved using uncertainty estimation.
• There is a set of expectations regarding how uncertainty should ``behave".