Blei Lab
@bleilab.bsky.social
Machine learning lab at Columbia University. Probabilistic modeling and approximate inference, embeddings, Bayesian deep learning, and recommendation systems.
🔗 https://www.cs.columbia.edu/~blei/
🔗 https://github.com/blei-lab
🔗 https://www.cs.columbia.edu/~blei/
🔗 https://github.com/blei-lab
Reposted by Blei Lab
i'm at ICLR this week
presenting at the morning poster session on thursday
excited to catch up with friends and collaborators, old and new
let's chat
presenting at the morning poster session on thursday
excited to catch up with friends and collaborators, old and new
let's chat
April 23, 2025 at 4:10 AM
i'm at ICLR this week
presenting at the morning poster session on thursday
excited to catch up with friends and collaborators, old and new
let's chat
presenting at the morning poster session on thursday
excited to catch up with friends and collaborators, old and new
let's chat
Check out our new paper about hypothesis testing the circuit hypothesis in LLMs! This work previously won a top paper award at the ICML mechanistic interpretability workshop, and we’re excited to share it at #Neurips2024
The circuit hypothesis proposes that LLM capabilities emerge from small subnetworks within the model. But how can we actually test this? 🤔
joint work with @velezbeltran.bsky.social @maggiemakar.bsky.social @anndvision.bsky.social @bleilab.bsky.social Adria @far.ai Achille and Caro
joint work with @velezbeltran.bsky.social @maggiemakar.bsky.social @anndvision.bsky.social @bleilab.bsky.social Adria @far.ai Achille and Caro
December 10, 2024 at 7:07 PM
Check out our new paper about hypothesis testing the circuit hypothesis in LLMs! This work previously won a top paper award at the ICML mechanistic interpretability workshop, and we’re excited to share it at #Neurips2024
Check out our new paper from the Blei Lab on probabilistic predictions with conditional diffusions and gradient boosted trees! #Neurips2024
I am very excited to share our new Neurips 2024 paper + package, Treeffuser! 🌳 We combine gradient-boosted trees with diffusion models for fast, flexible probabilistic predictions and well-calibrated uncertainty.
paper: arxiv.org/abs/2406.07658
repo: github.com/blei-lab/tre...
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paper: arxiv.org/abs/2406.07658
repo: github.com/blei-lab/tre...
🧵(1/8)
December 2, 2024 at 11:02 PM
Check out our new paper from the Blei Lab on probabilistic predictions with conditional diffusions and gradient boosted trees! #Neurips2024