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
Working on uncertainty quantification, few-shot learning, and probabilistic machine learning in general.
https://ruili-pml.github.io
Reposted by Rui Li
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
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
September 18, 2025 at 8:34 PM
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
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
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
April 21, 2025 at 1:31 PM
🎉 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
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
Reposted by Rui Li
Now that we put the camera-ready version on ArXiv, I will write a bit about this cool project.
We got an #ICLR paper 🎉!
Awesome work done with @ruili-pml.bsky.social, @marcusklasson.bsky.social, and @arnosolin.bsky.social.
More details will follow!!!
arxiv.org/abs/2411.18425
Awesome work done with @ruili-pml.bsky.social, @marcusklasson.bsky.social, and @arnosolin.bsky.social.
More details will follow!!!
arxiv.org/abs/2411.18425
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
March 19, 2025 at 9:32 AM
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!
Are you going to be at #WACV and want to know if “Flatness Improves Backbone Generalisation in Few-shot Classification”?
Then join the oral presentation by @ruili-pml.bsky.social of our paper!
🔗 lnkd.in/dBMmN7Vs
Done together with @marcusklasson.bsky.social and @arnosolin.bsky.social.
Then join the oral presentation by @ruili-pml.bsky.social of our paper!
🔗 lnkd.in/dBMmN7Vs
Done together with @marcusklasson.bsky.social and @arnosolin.bsky.social.
February 24, 2025 at 11:49 AM
Come check our presentation and paper!
🥳
We got an #ICLR paper 🎉!
Awesome work done with @ruili-pml.bsky.social, @marcusklasson.bsky.social, and @arnosolin.bsky.social.
More details will follow!!!
arxiv.org/abs/2411.18425
Awesome work done with @ruili-pml.bsky.social, @marcusklasson.bsky.social, and @arnosolin.bsky.social.
More details will follow!!!
arxiv.org/abs/2411.18425
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
January 27, 2025 at 11:48 AM
🥳
check our posters at BDU workshop!
I will present ✌️ BDU workshop papers @ NeurIPS: one by Rui Li (looking for internships) and one by Anton Baumann.
🔗 to extended versions:
1. 🙋 "How can we make predictions in BDL efficiently?" 👉 arxiv.org/abs/2411.18425
2. 🙋 "How can we do prob. active learning in VLMs" 👉 arxiv.org/abs/2412.06014
🔗 to extended versions:
1. 🙋 "How can we make predictions in BDL efficiently?" 👉 arxiv.org/abs/2411.18425
2. 🙋 "How can we do prob. active learning in VLMs" 👉 arxiv.org/abs/2412.06014
December 11, 2024 at 7:34 AM
check our posters at BDU workshop!