Andrew Saxe@SaxeLab

Prof at @GatsbyUCL and @SWC_Neuro, trying to figure out how we learn. Bluesky: @SaxeLab Mastodon: @SaxeLab@sigmoid.social

 London, UK
saxelab.org
Joined November 2019
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Andrew Saxe retweeted
Jamie Simon@learning_mech
Apr 24
1/ Deep learning is going to have a scientific theory. We can see the pieces starting to come together, and it's looking a lot like physics! We're releasing a paper pulling together these emerging threads and giving them a name: learning mechanics. 🔨 arxiv.org/pdf/2604.21691 🔧
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Come chat about this @iclr_conf, at 3:15 PM on Friday in Pavilion 4 Poster #4216!
Andrew Saxe@SaxeLab
Feb 3
Why don’t neural networks learn all at once, but instead progress from simple to complex solutions? And what does “simple” even mean across different neural network architectures? Sharing our new paper @iclr_conf led by Yedi Zhang with Peter Latham arxiv.org/abs/2512.20607
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Two Analytical Connectionism-related updates: 1. ⏰ 1 week left to apply! Interested in language + AI & cognition? Don’t miss it: analytical-connectionism.net… 2. 📜 Lecture notes from the first two editions are finally out: proceedings.mlr.press/v320/

2026 School on Analytical Connectionism

A 2-week summer course hosted at Chalmers University of Technology on analysing language acquisition and higher-level cognition.

analytical-connectionism.net
Stefano Sarao Mannelli@stefsmlab
Feb 18
📢 We’re now accepting applications for the 2026 School on Analytical Connectionism dedicated this year to Language Acquisition. 📍 Gothenburg, Sweden 🗓️ August 17–28, 2026 ☠️ Apply by April 17! 🔗 analytical-connectionism.net… 👇 Meet the experts joining us this summer!
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Postdoc opening! Come work with us on deep learning theory relevant to AI safety Deadline: 7 Apr 2026 Details and application: ucl.ac.uk/work-at-ucl/search…+

UCL – University College London

UCL is consistently ranked as one of the top ten universities in the world (QS World University Rankings 2010-2022) and is No.2 in the UK for research power (Research Excellence Framework 2021).

ucl.ac.uk
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Very excited by this year's Analytical Connectionism Summer School! A dream lineup of speakers on the topic of language acquisition in minds and machines Bursaries available to cover costs Aug 17 – Aug 28, 2026 Gothenburg Details: analytical-connectionism.net…
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Andrew Saxe retweeted
Francis Bach@BachFrancis
Mar 5
Looking for alternatives to quadratic functions for closed-form analysis in optimization? This post explores matrix Riccati dynamics and their applications to neural networks. francisbach.com/closed-form-…
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Andrew Saxe retweeted
Andrew Lampinen@AndrewLampinen
Feb 18
What is the relationship between memorization and generalization in AI? Is there a fundamental tradeoff? In a new blog post I’ve reviewed some of the evolving perspectives on memorization & generalization in machine learning, from classic perspectives through LLMs. Link below:
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📢 We’re now accepting applications for the 2026 School on Analytical Connectionism dedicated this year to Language Acquisition. 📍 Gothenburg, Sweden 🗓️ August 17–28, 2026 ☠️ Apply by April 17! 🔗 analytical-connectionism.net… 👇 Meet the experts joining us this summer!
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Hiring 2 Postdocs to work on Theoretical Foundations of AI Safety @chalmersuniv If you have a background in Physics, Math, or ML and want to tackle AI alignment at a fundamental level alongside UCL, apply below! 🔗Apply: chalmers.se/en/about-chalmer… 🔬Lab: stefsmlab.github.io/

Vacancies

chalmers.se
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Excited to launch Principia, a nonprofit research organisation at the intersection of deep learning theory and AI safety. Our goal is to develop theory for modern machine learning that can help us understand network behaviors, including those critical for AI safety. 1
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We’re hiring postdocs/research scientists! Your interests can be anywhere on the spectrum from pure theory to empirically testing predictions relevant to AI safety. Our theoretical work relies on dynamical systems and tools from statistical physics. 3
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How to apply: USD 80,000–100,000 (50-74k GBP) annualized 6 months, w/ extension based on funding Details: docs.google.com/document/d/1… Application: forms.gle/xKukH74iX16pPGrA6 4

[Hiring] Principia Research Fellows

Principia Research Fellows: Theoretical Model Organisms for AI Safety Principia · London · Fixed-term (6 months) with potential extension · Starting ASAP We are launching Principia, a new technical...

docs.google.com
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Why don’t neural networks learn all at once, but instead progress from simple to complex solutions? And what does “simple” even mean across different neural network architectures? Sharing our new paper @iclr_conf led by Yedi Zhang with Peter Latham arxiv.org/abs/2512.20607
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Equipped with this theory, we make new predictions about how network width, data distribution, and initialization affect learning dynamics. For example, increasing the number of attention heads in linear attention shortens the plateaus in learning.
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Upcoming online talk next Monday 9th February, at the ELLIS Reading Group on Mathematics & Efficiency of Deep Learning! Open to all. Info at sites.google.com/view/effici…

DLMath&Efficiency

A public ELLIS reading group exploring the interplay between the mathematical foundations of deep learning and the practical challenge of making ML efficient — from optimization theory to hardware-...

sites.google.com
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