iiinova — where your digital self keeps evolving

Reposted by Michael Albergo

Dr. Lucky Tran @luckytran.com · 11/07/2025

DO NOT GIVE UP! Our advocacy is working. A key Senate committee has indicated that it will reject Trump’s proposed cuts to science agencies including NASA and the NSF. Keep speaking up and calling your electeds 🗣️🗣️🗣️

Nature: US senators poised to reject Trump’s proposed massive science cuts

Committee gives first hint that policymakers might preserve, rather than slash, funding for US National Science Foundation and other agencies.

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Reposted by Michael Albergo

Anthony Costa @anthonybcosta.bsky.social · 28/04/2025

Congratulations to Peter Holderrieth @msalbergo.bsky.social and Tommi Jaakkola for winning the best paper award for their work entitled "LEAPS: A discrete neural sampler via locally equivariant networks" at this year's Frontiers in Probabilistic Inference workshop #ICLR2025!

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Michael Albergo @msalbergo.bsky.social · 24/04/2025

Excited to be at @iclrconf for #ICLR2025! I’ll give a talk at the Frontiers on Probabilistic Inference workshop to discuss work with @evdende2, @peholderrieth, @brianlee_lck, @jeha_paul, and Francisco Vargas! Let me know about your work, I will come by :)

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Reposted by Michael Albergo

Grant Rotskoff @grant.rotskoff.cc · 23/12/2024

I am hiring a postdoctoral scholar with a start date summer or fall 2025. Projects will be focused on thermodynamically consistent generative models, broadly defined. If you’re interested, please send a CV and one paragraph about why you think you’d be a good fit to rotskoff@stanford.edu

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Michael Albergo @msalbergo.bsky.social · 06/12/2024

We got a preview of this stuff just a few days ago at the CECAM workshop. This is really cool stuff from @franknoe.bsky.social and co. Congrats!

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Reposted by Michael Albergo

Gabriel Peyré @gabrielpeyre.bsky.social · 03/12/2024

Hellinger and Wasserstein are the two main geodesic distances on probability distributions. While both minimize the same energy, they differ in their interpolation methods: Hellinger focuses on density, whereas Wasserstein emphasizes position displacements.

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Reposted by Michael Albergo

Grant Rotskoff @grant.rotskoff.cc · 03/12/2024

If you're at NeurIPS next week come see our spotlight poster led by Yinuo Ren and Haoxuan Chen! We use the parallel sampling technique to rigorously establish a big acceleration for diffusion model inference! neurips.cc/virtual/2024...

neurips.cc

NeurIPS Poster Accelerating Diffusion Models with Parallel Sampling: Inference at Sub-Linear Time ComplexityNeurIPS 2024

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Reposted by Michael Albergo

ruiqigao.bsky.social @ruiqigao.bsky.social · 02/12/2024

A common question nowadays: Which is better, diffusion or flow matching? 🤔 Our answer: They’re two sides of the same coin. We wrote a blog post to show how diffusion models and Gaussian flow matching are equivalent. That’s great: It means you can use them interchangeably.

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Michael Albergo @msalbergo.bsky.social · 21/11/2024

Hello BlueSky! If and when I'm posting online, I'll be sure to do it here too.

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