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Louis Pezon

@lpezon.bsky.social
84 followers 21 following 11 posts

PhD student in computational & theoretical neuroscience, with Wulfram Gerstner @ EPFL. Theories of computation via low-dimensional dynamics in recurrent neural networks.

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Louis Pezon @lpezon.bsky.social · 28/09/2026
How can RNNs re-use the same dynamics across different tasks to implement compositional computation? What are the consequences for network connectivity & activity? If you're interested, come and find out at the Bernstein Conference, poster session III-#48!
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Reposted by Louis Pezon
GerstnerLab @gerstnerlab.bsky.social · 29/06/2026
How can the brain learn the hidden hierarchical structure from high dimensional data? In our latest work, we use synthetic datasets to analyze two classes of bio-plausible learning rules: variants of Direct Feedback Alignment, and local self-supervised learning. We find only the latter succeeds.
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Louis Pezon @lpezon.bsky.social · 30/06/2026
Both brains and RNNs can re-use components of computation across similar tasks or contexts. But what exactly are those “shared components”? How can they be used to solve several tasks? We address these questions in a new preprint with @avm.bsky.social! Link: www.biorxiv.org/content/10.6...
biorxiv.org
Interpretable compositional computation with recurrent neural networks
Flexible cognition utilizes reusable components to enable rapid adaptation of behavior to different contexts or tasks. Analysis of artificial neural networks trained on multiple tasks suggested that t...
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Reposted by Louis Pezon
Flavio Martinelli @flavioh.bsky.social · 10/06/2026
NEW PAPER. Why do larger networks train better? "Because they contain more candidate *sub*networks that can learn the task" → lottery tickets This popular explanation uses an appealing but misleading metaphor🧵 We propose an intuitive alternative grounded in theory: escape dimensions
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Reposted by Louis Pezon
Valentin Schmutz @bio-emergent.bsky.social · 08/05/2026
Unbelievably honoured to read Tatiana Engel's (@engeltatiana.bsky.social) wonderfully written Preview on our work "Linking neural manifolds to circtuit structure in recurrent networks" (with @lpezon.bsky.social & @gerstnerlab.bsky.social) in this issue of Neuron www.cell.com/neuron/fullt... 🙏
cell.com
Finding clues to circuit structure in population dynamics and single-neuron selectivity
In this issue of Neuron, Pezon et al. introduce neural circuit models with flexible connectivity structure that can generate low-dimensional population dynamics with different distributions of single-...
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Louis Pezon @lpezon.bsky.social · 13/03/2026
Presenting a poster tomorrow at Cosyne 26: [3-033] Compositional computation via shared latent dynamics in low-rank RNNs. With @avm.bsky.social, we explore how RNNs can re-use the same dynamics across different tasks, and what it implies for their connectivity and neural activity.
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Reposted by Louis Pezon
Alexander van Meegen @avm.bsky.social · 12/03/2026
Travelling to COSYNE seems to be the perfect opportunity to announce that I started my own lab at RWTH Aachen University earlier this year, funded by NRW's Ministry of Culture and Science through its Return Program. If you are at COSYNE and want to chat please reach out!
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Louis Pezon @lpezon.bsky.social · 06/03/2026
Excited to share our new paper to be published in Neuron! With Valentin Schmutz @bio-emergent.bsky.social and Wulfram Gerstner @gerstnerlab.bsky.social, we explore how circuit structure in RNNs shapes network computation and single-neuron responses. www.sciencedirect.com/science/arti...
sciencedirect.com
Linking neural manifolds to circuit structure in recurrent networks
Dimensionality reduction methods are widely used in neuroscience to investigate two complementary aspects of neural activity: the distribution of sing…
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