Working in mechanistic interpretability, nlp, causal inference, and probabilistic modeling!
Previously at Meta for ~3 years on the Bayesian Modeling & Generative AI teams.
🔗 www.sweta.dev
Join us Feb 11th @ 4pm for Romain Lopez!
www.eventbrite.com/e/ml-nyc-spe...
Join us Feb 11th @ 4pm for Romain Lopez!
Registration: www.eventbrite.com/e/ml-nyc-spe...
Registration: www.eventbrite.com/e/ml-nyc-spe...
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
come chat with Nicolas , @swetakar.bsky.social , Quentin , Jannik , and i today
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
come chat with Nicolas , @swetakar.bsky.social , Quentin , Jannik , and i today
paper: arxiv.org/abs/2406.07658
repo: github.com/blei-lab/tre...
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joint work with @velezbeltran.bsky.social @maggiemakar.bsky.social @anndvision.bsky.social @bleilab.bsky.social Adria @far.ai Achille and Caro
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paper: arxiv.org/abs/2406.07658
repo: github.com/blei-lab/tre...
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Link: blog.neurips.cc/2024/11/27/a...
Link: blog.neurips.cc/2024/11/27/a...
www.bewitched.com/demo/gini
www.bewitched.com/demo/gini
Timo and I recently published a book, and even if you are not a scientist, you'll find useful overviews of topics like causality and robustness.
The best part is that you can read it for free: ml-science-book.com
Timo and I recently published a book, and even if you are not a scientist, you'll find useful overviews of topics like causality and robustness.
The best part is that you can read it for free: ml-science-book.com
Let's start with "What are embeddings" by @vickiboykis.com
The book is a great summary of embeddings, from history to modern approaches.
The best part: it's free.
Link: vickiboykis.com/what_are_emb...
Let's start with "What are embeddings" by @vickiboykis.com
The book is a great summary of embeddings, from history to modern approaches.
The best part: it's free.
Link: vickiboykis.com/what_are_emb...
Please give us a follow! @bleilab.bsky.social
Please give us a follow! @bleilab.bsky.social