Unfortunately, our submission to #NeurIPS didn’t go through with (5,4,4,3). But because I think it’s an excellent paper, I decided to share it anyway. We show how to efficiently apply Bayesian learning in VLMs, improve calibration, and do active learning. Cool stuff! 📝 arxiv.org/abs/2412.06014

🎉 Presenting “Streamlining Prediction in Bayesian Deep Learning” at #ICLR2025! We replace MC estimation with local linearisation + Gaussian approximations → analytic posterior predictive in one forward pass. Fast, performs well, and scales to ViT. 📄 arxiv.org/abs/2411.18425 💻 github.com/AaltoML/SUQ

Now that we put the camera-ready version on ArXiv, I will write a bit about this cool project.

Come check our presentation and paper!

🥳

check our posters at BDU workshop!