Blei Lab
@bleilab.bsky.social
Machine learning lab at Columbia University. Probabilistic modeling and approximate inference, embeddings, Bayesian deep learning, and recommendation systems. đź”— https://www.cs.columbia.edu/~blei/ đź”— https://github.com/blei-lab
The ML in NYC Speaker Series + Happy Hour is excited to host Professor Romain Lopez as our February speaker as he discusses deep generative models and their applications to the field of cellular and molecular biology! www.eventbrite.com/e/ml-nyc-spe...
ML-NYC Speaker Series and Happy Hour: Romain Lopez
Learning from Millions of Cells with Deep Generative Models
eventbrite.com
ML-NYC Talk at the Flatiron Institute on December 10th! Come hear Professor Björkegren talk about AI for low income countries and how to rigorously measure whether technology does good or harm. There will be a reception afterwards for all guests. Register below if you’re interested in attending!
Sweta Karlekar@swetakar.bsky.social · 8mo agoThe ML in NYC Speaker Series + Happy Hour is excited to host Professor Daniel Björkegren as our December speaker as he speaks about AI for Low-Income Countries! Registration: www.eventbrite.com/e/ml-nyc-spe...
Excited to highlight recent work from the lab at NeurIPS! If you’re interested in understanding why uncertainty estimates often break under distribution shift — and how we can do better — check out Yuli’s poster tomorrow.
Yuli Slavutsky@yulislavutsky.bsky.social · 8mo agoUncertainty estimation fails under distribution shifts. Why? Partly because in stats, even Bayesian stats, we treat x as given. But intuitively data makes different models plausible. For reliable uncertainty, we need to account for it explicitly. Come chat with me about it tomorrow at my poster
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
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
claudia shi@claudiashi.bsky.social · 2y agoThe 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
Check out our new paper from the Blei Lab on probabilistic predictions with conditional diffusions and gradient boosted trees! #Neurips2024
Nicolas Beltran-Velez@velezbeltran.bsky.social · 2y agoI 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... 🧵(1/8)
