Check out Michael Kirchhof's 🧵 on pretrained and modular uncertainty quantification at scale!

If you've been using formulas like this to split aleatoric from epistemic uncertainty: They don't work. To find out why, come visit our poster #68 at the #ICML2024 #SPIGM workshop at 15:10! Michael Kirchhof Seong Joon Oh

Throughout my PhD, I've found one basic trick to read papers in less than 30 minutes but with maximum utility. It boils down to consuming actively, not passively: 🧵 1/5

Excited to present our spotlight paper on uncertainty disentanglement at #NeurIPS! Drop by today between 11 am and 2 pm PST at West Ballroom A-D #5509 and let's chat!

Have you wondered why I've posted all these nice plots and animations? 🤔 Well, the slides for my lectures on (Bayesian) Active Learning, Information Theory, and Uncertainty are online now! They cover quite a bit from basic information theory to some recent papers 🥳