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Professor at the Gatsby Unit and Sainsbury Wellcome Centre, UCL, trying to figure out how we learn
Andrew Saxe
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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: www.ucl.ac.uk/work-at-ucl/...
The First 1,000 Days (1kD) Project - Collecting and Analyzing an Ultra-Dense Naturalistic Dataset of Human Baby Development https://www.biorxiv.org/content/10.64898/2026.03.19.712982v1
2mo
A great entry into the proposals available for physiologically plausible gradient descent! I think the way they use dendrite targeting inhibition in this model is particularly elegant. Time to start testing these ideas folks!!! #neuroscience 🧪 #NeuroAI
2mo
New preprint! 🧠 How do RNNs learn abstract rules from sequences, independent of specific stimuli? By Vezha Boboeva, with Alberto Pezzotta & George Dimitriadis "From sequences to schemas: low-rank recurrent dynamics underlie abstract relational representations" www.biorxiv.org/content/10.6...
2mo
2mo
Two Analytical Connectionism-related updates: 1. ⏰ 1 week left to apply! Interested in language + AI & cognition? Don’t miss it: www.analytical-connectionism.net/school/2026/ 2. 📜 Lecture notes from the first two editions are finally out: proceedings.mlr.press/v320/
Andrew Saxe
bioRxiv Neuroscience
2mo
We’ve got an exciting new thing to share! We have causal evidence (using TMR) that memory reactivation during sleep promotes abstract understanding of underlying structure, allowing transfer learning in a new domain with zero superficial feature overlap with the learned one.
Come chat about this @iclr-conf.bsky.social! Friday 3:15 PM, Pavilion 4, Poster #4216
Blake Richards
2mo
Athena Akrami
1mo
1/7 Excited to share my last PhD article, just accepted to ICML 2026! In it, we (me, Alexandre Payeur, Guillaume Lajoie) used dynamical systems theory to study "local" learning in linear recurrent neural networks. See link for the paper, and thread for a brief summary. arxiv.org/abs/2606.00243
2d
Biological and neuromorphic recurrent neural networks (RNNs) are subject to spatial and temporal locality constraints on the information that can plausibly be used during learning. A common strategy t...
Dynamics and Representation Structure of Local Approximations to Gradient-Based Learning in Linear Recurrent Neural Networks
arxiv.org
Stefano Sarao Mannelli
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: www.analytical-connectionism.net//school/2026/
2mo
Yedi Zhang
Andrew Saxe
Anna Schapiro