I'm late to the party, but I loved @randomwalker.bsky.social's annotated ICML keynote slides. He clearly puts into words so many vague thoughts I had (and didn't have). Highly recommended! It's a great preparation to answer my relatives’ actual questions about AI, unlike my own work 😅

Arvind Narayanan@randomwalker.bsky.social · 3w ago

I had the honor of giving a keynote at the International Conference on Machine Learning last week. I addressed the widespread anxiety about how we should adapt as AI capabilities increase. I was thrilled by the talk’s reception, so I have made my slides available www.cs.princeton.edu/~arvindn/tal...

Applications are open for the Junior Theoretical Neuroscientists Workshop which will take place July 21-24, 2026 at the Center for Computational Neuroscience, @flatironinstitute.org Travel, lodging, and meals will be covered for accepted participants. Application deadline: April 15, 2026

📣 Excited to co-organize the 2nd Workshop on Scientific Methods for Understanding Deep Learning at ICLR in Rio de Janeiro, Brazil (April 26 or 27, 2026)!! 🔎🤖 🇧🇷 If you work on the why/how of deep learning, we are looking forward to reading your submission! 👇 #ICLR2026 #Sci4DL

I'll be in #NeurIPS2025 Dec 3-7, do reach out (atconf/email) if you want to chat (see below)! I'm on the faculty job market 👀 Come say hi to @zahra-kadkhodaie.bsky.social @eerosim.bsky.social and I at our poster on energy-based models Fri 11am #3700 (thread in quoted post) bsky.app/profile/flor...

Florentin Guth@florentinguth.bsky.social · last yr.

What is the probability of an image? What do the highest and lowest probability images look like? Do natural images lie on a low-dimensional manifold? In a new preprint with Zahra Kadkhodaie and @eerosim.bsky.social, we develop a novel energy-based model in order to answer these questions: 🧵

CDS Faculty Fellow @florentinguth.bsky.social, CDS PhD alum Zahra Kadkhodaie, & CDS Professor @eerosim.bsky.social, in a NeurIPS 2025 paper, estimate image probability directly & discover natural images differ in probability by factors of up to 10^14,000. nyudatascience.medium.com/when-ai-lear...

When AI Learns What Makes an Image Probable, Simple Beats Complex by 10¹⁴⁰⁰⁰

Natural images vary in probability by up to 10¹⁴⁰⁰⁰, CDS researchers find, challenging assumptions about how images are structured.

nyudatascience.medium.com

🔥 Mark your calendars for the next session of the @ellis.eu x UniReps Speaker Series! 🗓️ When: 31th July – 16:00 CEST 📍 Where: ethz.zoom.us/j/66426188160 🎙️ Speakers: Keynote by @pseudomanifold.topology.rocks & Flash Talk by @florentinguth.bsky.social

Next appointment: 31st July 2025 – 16:00 CEST on Zoom with 🔵Keynote: @pseudomanifold.topology.rocks (University of Fribourg) 🔴 @florentinguth.bsky.social (NYU & Flatiron)

What is the probability of an image? What do the highest and lowest probability images look like? Do natural images lie on a low-dimensional manifold? In a new preprint with Zahra Kadkhodaie and @eerosim.bsky.social, we develop a novel energy-based model in order to answer these questions: 🧵

🌈 I'll be presenting our JMLR paper "A rainbow in deep network black boxes" today at 3pm at @iclr-conf.bsky.social! Come to poster #334 if you're interested, I'll be happy to chat More details in the threads on the other website: x.com/FlorentinGut...

A loose thought that's been bubbling around for me recently: when you think of a 'generic' big matrix, you might think of it as being close to low-rank (e.g. kernel matrices), or very far from low-rank (e.g. the typical scope of random matrix theory). Intuition ought to be quite different in each.

Speaking at this #NeurIPS2024 workshop on a new analytic theory of creativity in diffusion models that predicts what new images they will create and explains how these images are constructed as patch mosaics of the training data. Great work by @masonkamb.bsky.social scienceofdlworkshop.github.io

Excited to present work with @jfeather.bsky.social @eerosim.bsky.social and @sueyeonchung.bsky.social today at Neurips! May do a proper thread later on, but come by or shoot me a message if you are in Vancouver and want to chat :) Brief details in post below

I'll be at @neuripsconf.bsky.social from Tuesday to Sunday! Feel free to reach out (Whova, email, DM) if you want to chat about scientific/theoretical understanding of deep learning, diffusion models, or more! (see below) And check out our Sci4DL workshop on Sunday: scienceofdlworkshop.github.io