Accurately tracking atmospheric greenhouse gases requires not only fast predictions but also reliable estimates of uncertainty.

AI models aren’t infallible; that’s why a prediction is often accompanied by a confidence score. Thanks to a recent study, these uncertainty estimates are now more accurate, efficient and scalable.

I'm doing some sensor fusion work (EG, if I have several location sensors that don't 100% agree with each other, what is the best guess for where you actually are?) I would like to figure out a data ...