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Rui Li

@ruili-pml.bsky.social

PhD student at Aalto University. Working on uncertainty quantification, few-shot learning, and probabilistic machine learning in general. https://ruili-pml.github.io

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Martin Trapp@trappmartin.eurosky.social · 12mo ago

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

Post-hoc Probabilistic Vision-Language Models

Vision-language models (VLMs), such as CLIP and SigLIP, have found remarkable success in classification, retrieval, and generative tasks. For this, VLMs deterministically map images and text descripti...

arxiv.org

Rui Li@ruili-pml.bsky.social · last yr.

🎉 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

Streamlining Prediction in Bayesian Deep Learning

The rising interest in Bayesian deep learning (BDL) has led to a plethora of methods for estimating the posterior distribution. However, efficient computation of inferences, such as predictions, has b...

arxiv.org