Nicolas Beltran-Velez
@velezbeltran.bsky.social
Machine Learning PhD Student
@ Blei Lab & Columbia University.
Working on probabilistic ML | uncertainty quantification | LLM interpretability.
Excited about everything ML, AI and engineering!
@ Blei Lab & Columbia University.
Working on probabilistic ML | uncertainty quantification | LLM interpretability.
Excited about everything ML, AI and engineering!
I just wanted to see what it looked like 😭
February 19, 2025 at 2:26 AM
I just wanted to see what it looked like 😭
Hello!
We will be presenting Estimating the Hallucination Rate of Generative AI at NeurIPS. Come if you'd like to chat about epistemic uncertainty for In-Context Learning, or uncertainty more generally. :)
Location: East Exhibit Hall A-C #2703
Time: Friday @ 4:30
Paper: arxiv.org/abs/2406.07457
We will be presenting Estimating the Hallucination Rate of Generative AI at NeurIPS. Come if you'd like to chat about epistemic uncertainty for In-Context Learning, or uncertainty more generally. :)
Location: East Exhibit Hall A-C #2703
Time: Friday @ 4:30
Paper: arxiv.org/abs/2406.07457
December 12, 2024 at 6:13 PM
Hello!
We will be presenting Estimating the Hallucination Rate of Generative AI at NeurIPS. Come if you'd like to chat about epistemic uncertainty for In-Context Learning, or uncertainty more generally. :)
Location: East Exhibit Hall A-C #2703
Time: Friday @ 4:30
Paper: arxiv.org/abs/2406.07457
We will be presenting Estimating the Hallucination Rate of Generative AI at NeurIPS. Come if you'd like to chat about epistemic uncertainty for In-Context Learning, or uncertainty more generally. :)
Location: East Exhibit Hall A-C #2703
Time: Friday @ 4:30
Paper: arxiv.org/abs/2406.07457
December 3, 2024 at 4:16 PM
Algo 1 (training)
tinyurl.com/treeffuser-s...
tinyurl.com/treeffuser-s...
December 3, 2024 at 4:16 PM
Algo 1 (training)
tinyurl.com/treeffuser-s...
tinyurl.com/treeffuser-s...
Treeffuser is also on pip!
(7/8)
(7/8)
December 2, 2024 at 9:48 PM
Treeffuser is also on pip!
(7/8)
(7/8)
Check out our paper (link below) for experiments on UCI datasets and a real-world application in sales forecasting using Walmart data.
paper: arxiv.org/abs/2406.07658
(6/8)
paper: arxiv.org/abs/2406.07658
(6/8)
December 2, 2024 at 9:48 PM
Check out our paper (link below) for experiments on UCI datasets and a real-world application in sales forecasting using Walmart data.
paper: arxiv.org/abs/2406.07658
(6/8)
paper: arxiv.org/abs/2406.07658
(6/8)
Our model requires little to no tuning, adapts to any distribution, and is very easy to use—just three lines of code!
(5/8)
(5/8)
December 2, 2024 at 9:48 PM
Our model requires little to no tuning, adapts to any distribution, and is very easy to use—just three lines of code!
(5/8)
(5/8)
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...
🧵(1/8)
paper: arxiv.org/abs/2406.07658
repo: github.com/blei-lab/tre...
🧵(1/8)
December 2, 2024 at 9:48 PM
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...
🧵(1/8)
paper: arxiv.org/abs/2406.07658
repo: github.com/blei-lab/tre...
🧵(1/8)
I like this (kind of trivial) formalization of the linear representation hypothesis. Not sure if it's entirely correct or complete, but I prefer it to the verbal descriptions I often see.
November 19, 2024 at 2:03 PM
I like this (kind of trivial) formalization of the linear representation hypothesis. Not sure if it's entirely correct or complete, but I prefer it to the verbal descriptions I often see.
As I understand it means something along these lines which seems to me a bit different.
November 18, 2024 at 5:30 PM
As I understand it means something along these lines which seems to me a bit different.