Monte Carlo Dropout

Is your algorithm confident enough? How to measure uncertainty in neural networks

When machine learning techniques are used in “mission critical” applications, the acceptable margin of error becomes significantly lower.

Imagine that your model is driving a car, assisting a doctor or even just interacting directly with an (perhaps easily annoyed) end user. In these cases, you’ll want to ensure that you can be confident in the predictions your model makes before acting on them.