Arnaud Doucet
Senior Staff Research Scientist @Google DeepMind, former Chair Prof @Oxford Uni
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- Really interesting paper indeed.
- 🔥 WANTED: Student Researcher to join me, @vdebortoli.bsky.social, Jiaxin Shi, Kevin Li and @arthurgretton.bsky.social in DeepMind London. You'll be working on Multimodal Diffusions for science. Apply here google.com/about/career...
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- Really nice.
- Reposted by Arnaud DoucetVery excited to share our preprint: Self-Speculative Masked Diffusions We speed up sampling of masked diffusion models by ~2x by using speculative sampling and a hybrid non-causal / causal transformer arxiv.org/abs/2510.03929 w/ @vdebortoli.bsky.social, Jiaxin Shi, @arnauddoucet.bsky.social
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- Reposted by Arnaud DoucetShunichi Amari has been awarded the 40th (2025) Kyoto Prize in recognition of his pioneering research in the fields of artificial neural networks, machine learning, and information geometry www.riken.jp/pr/news/2025...
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- Reposted by Arnaud DoucetWhy academia is sleepwalking into self-destruction. My editorial @brain1878.bsky.social If you agree with the sentiments please repost. It's important for all our sakes to stop the madness academic.oup.com/brain/articl...
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- Great intro to PAC-Bayes bounds. Highly recommended!
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- A standard ML approach for parameter estimation in latent variable models is to maximize the expectation of the logarithm of an importance sampling estimate of the intractable likelihood. We provide consistency/efficiency results for the resulting estimate: arxiv.org/abs/2501.08477
- Speculative sampling accelerates inference in LLMs by drafting future tokens which are verified in parallel. With @vdebortoli.bsky.social , A. Galashov & @arthurgretton.bsky.social , we extend this approach to (continuous-space) diffusion models: arxiv.org/abs/2501.05370
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- The slides of my NeurIPS lecture "From Diffusion Models to Schrödinger Bridges - Generative Modeling meets Optimal Transport" can be found here drive.google.com/file/d/1eLa3...
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