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Reposted by Cengiz Pehlevan

arXiv q-bio.NC Neurons and Cognition @qbionc-bot.bsky.social · 10d

William Qian, Cengiz Pehlevan: Discovering alternative solutions beyond the simplicity bias in recurrent neural networks https://arxiv.org/abs/2509.21504 https://arxiv.org/pdf/2509.21504 https://arxiv.org/html/2509.21504

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Reposted by Cengiz Pehlevan

Data on the Brain & Mind @NeurIPS2025 @dataonbrainmind.bsky.social · Sep 7

⏳ Less than 1 day left until the Brain & Mind Workshop submission deadline!
🔍 Submit to our Finding or Tutorials track on OpenReview.
Findings track submission: openreview.net/group?id=Neu...
Tutorial track submission: openreview.net/group?id=Neu...
More info: data-brain-mind.github.io

NeurIPS 2025 Workshop DBM Findings

Welcome to the OpenReview homepage for NeurIPS 2025 Workshop DBM Findings

openreview.net

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Cengiz Pehlevan @cpehlevan.bsky.social · Sep 7

Thank you so much for the kind shoutout! Grateful to be part of such a fantastic team.

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Jacob Zavatone-Veth @jzv.bsky.social · Sep 4

Since I'm back on BlueSky - with @frostedblakess.bsky.social and @cpehlevan.bsky.social we wrote a brief perspective on how ideas about summary statistics from the statistical physics of learning could potentially help inform neural data analysis... (1/2)

Frontiers | Summary statistics of learning link changing neural representations to behavior

How can we make sense of large-scale recordings of neural activity across learning? Theories of neural network learning with their origins in statistical phy...

www.frontiersin.org

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Venki Murthy @neurovenki.bsky.social · Sep 4

Excited to share new computational work, led by @jzv.bsky.social, driven by Juan Carlos Fernandez del Castillo + contribution from Farhad Pashakanloo. We recover 3 core motifs in the olfactory system of evolutionarily distant animals using a biophysically-grounded model + efficient coding ideas!

Convergent motifs of early olfactory processing are recapitulated by layer-wise efficient coding

The architecture of early olfactory processing is a striking example of convergent evolution. Typically, a panel of broadly tuned receptors is selectively expressed in sensory neurons (each neuron exp...

www.biorxiv.org

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Reposted by Cengiz Pehlevan

Patrick Shafto @patrickshafto.bsky.social · Sep 2

Great to have this video about my @darpa.mil Artificial Intelligence Quantified (AIQ) program out! Very exciting program with absolutely fantastic teams. Stay tuned for some jaw dropping announcements!

www.youtube.com/watch?v=KVRF...

AIQ: Artificial Intelligence Quantified

YouTube video by DARPAtv

www.youtube.com

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Reposted by Cengiz Pehlevan

M Ganesh Kumar @mgkumar138.bsky.social · Aug 27

I am extremely grateful to be awarded the National University of Singapore (NUS) Development Grant, and to be a Young NUS Fellow! Look forward to collaborating with the Yong Loo Lin School of Medicine on exciting projects. This is my first grant and hopefully many more to come! #NUS #NeuroAI

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Reposted by Cengiz Pehlevan

Simons Foundation @simonsfoundation.org · Aug 19

Our new Simons Collaboration on the Physics of Learning and Neural Computation will develop powerful tools from #physics, #math, computer science and theoretical #neuroscience to understand how large neural networks learn, compute, scale, reason and imagine: www.simonsfoundation.org/2025/08/18/s...

Simons Foundation Launches Collaboration on the Physics of Learning and Neural Computation

Simons Foundation Launches Collaboration on the Physics of Learning and Neural Computation on Simons Foundation

www.simonsfoundation.org

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Sam Gershman @gershbrain.bsky.social · Aug 18

If you work on artificial or natural intelligence and are finishing your PhD, consider applying for a Kempner research fellowship at Harvard:
kempnerinstitute.harvard.edu/kempner-inst...

Kempner Research Fellowship - Kempner Institute

The Kempner brings leading, early-stage postdoctoral scientists to Harvard to work on projects that advance the fundamental understanding of intelligence.

kempnerinstitute.harvard.edu

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Reposted by Cengiz Pehlevan

Kempner Institute at Harvard University @kempnerinstitute.bsky.social · Aug 18

Congratulations to #KempnerInstitute associate faculty member @cpehlevan.bsky.social for joining the new
@simonsfoundation.org Simons Collaboration on the Physics of Learning and Neural Computation!

www.simonsfoundation.org/2025/08/18/s...

#AI #neuroscience #NeuroAI #physics #ANNs

Simons Foundation Launches Collaboration on the Physics of Learning and Neural Computation

Simons Foundation Launches Collaboration on the Physics of Learning and Neural Computation on Simons Foundation

www.simonsfoundation.org

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Reposted by Cengiz Pehlevan

Surya Ganguli @suryaganguli.bsky.social · Aug 18

Very excited to lead this new @simonsfoundation.org collaboration on the physics of learning and neural computation to develop powerful tools from physics, math, CS, stats, neuro and more to elucidate the scientific principles underlying AI. See our website for more: www.physicsoflearning.org

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Data on the Brain & Mind @NeurIPS2025 @dataonbrainmind.bsky.social · Aug 4

🚨 Excited to announce our #NeurIPS2025 Workshop: Data on the Brain & Mind

📣 Call for: Findings (4- or 8-page) + Tutorials tracks

🎙️ Speakers include @dyamins.bsky.social @lauragwilliams.bsky.social @cpehlevan.bsky.social

🌐 Learn more: data-brain-mind.github.io

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Reposted by Cengiz Pehlevan

Kempner Institute at Harvard University @kempnerinstitute.bsky.social · Jul 28

The post is based on a paper written with Yue M. Lu., @jzv.bsky.social, Anindita Maiti and @cpehlevan.bsky.social evan.

Check it out now at PNAS:

doi.org/10.1073/pnas...

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PNAS

Proceedings of the National Academy of Sciences (PNAS), a peer reviewed journal of the National Academy of Sciences (NAS) - an authoritative source of high-impact, original research that broadly spans...

doi.org

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Reposted by Cengiz Pehlevan

Kempner Institute at Harvard University @kempnerinstitute.bsky.social · Jul 28

New in the #DeeperLearningBlog: the #KempnerInstitute's Mary Letey presents work recently published in PNAS that offers generalizable insights into in-context learning (ICL) in an analytically-solvable model architecture.

bit.ly/4lPK15p

#AI @pnas.org

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Solvable Model of In-Context Learning Using Linear Attention - Kempner Institute

Attention-based architectures are a powerful force in modern AI. In particular, the emergence of in-context learning enables these models to perform tasks far beyond the original next-token prediction...

kempnerinstitute.harvard.edu

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Reposted by Cengiz Pehlevan

Anirvan Sengupta @anirvansengupta.bsky.social · Jul 16

At #ICML2025, presenting work done at @flatironinstitute.org w Matt Smart and @albertobietti.bsky.social on in-context denoising (arxiv.org/abs/2502.05164). Come to Matt’s oral, Thursday, 4:15-4:30 PM, West Ballroom A, and see us right after at poster #E-3207, 4:30-7:00 PM, East Exhibition Hall A-B.

In-context denoising with one-layer transformers: connections between attention and associative memory retrieval

We introduce in-context denoising, a task that refines the connection between attention-based architectures and dense associative memory (DAM) networks, also known as modern Hopfield networks. Using a...

arxiv.org

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Cengiz Pehlevan @cpehlevan.bsky.social · Jul 11

Great to see this one finally out in PNAS! Asymptotic theory of in-context learning by linear attention www.pnas.org/doi/10.1073/... Many thanks to my amazing co-authors Yue Lu, Mary Letey, Jacob Zavatone-Veth @jzv.bsky.social and Anindita Maiti!

Asymptotic theory of in-context learning by linear attention | PNAS

Transformers have a remarkable ability to learn and execute tasks based on examples provided within the input itself, without explicit prior traini...

www.pnas.org

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SfN Journals @sfnjournals.bsky.social · Jun 13

#eNeuro: Obeid and Miller identify distinct neural computations in the primary visual cortex that explain how surrounding context suppresses perception of visual figures and features. �€ª@harvardseas.bsky.social‬ vist.ly/3n6tfb2

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David Lipshutz @lipshutz.bsky.social · Apr 9

📣 Grad students and postdocs in computational and theoretical neuroscience: please consider applying for the 2025 Flatiron Institute Junior Theoretical Neuroscience Workshop! All expenses are covered. Apply by April 14. jtnworkshop2025.flatironinstitute.org

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M Ganesh Kumar @mgkumar138.bsky.social · Mar 27

New preprint! We trained an RNN using RL to solve a decision making task used to characterize suboptimal decision making by Schizophrenic patients. First project exploring comp psych models, thanks to @adam-manoogian.bsky.social @shawnrhoadsphd.bsky.social @bqian.bsky.social @cpehlevan.bsky.social

bioRxiv Neuroscience @biorxiv-neursci.bsky.social · Mar 14

Neurocomputational underpinnings of suboptimal beliefs in recurrent neural network-based agents https://www.biorxiv.org/content/10.1101/2025.03.13.642273v1

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Cengiz Pehlevan @cpehlevan.bsky.social · Feb 19

Congratulations!

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Reposted by Cengiz Pehlevan

Paul Masset @paulmasset.bsky.social · Feb 18

Honoured to have been selected as a #SloanFellow
Thankful for all the support from family, mentors, collaborators, colleagues and students along the way!
@sloanfoundation.bsky.social

McGill University @mcgill.ca · Feb 18

Professors Paul Masset and David Rolnick awarded 2025 Alfred P. Sloan Research Fellowships ✨ Their work ‘exemplifies McGill’s leadership in AI research and innovation.’ Since 1955, 33 McGill faculty members have received this honour.

Read more: mcgill.ca/x/iZ4

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David G. Clark @david-g-clark.bsky.social · Jan 29

(1/30) New preprint! "Symmetries and continuous attractors in disordered neural circuits" with Larry Abbott and Haim Sompolinsky
bioRxiv: www.biorxiv.org/content/10.1...

Symmetries and Continuous Attractors in Disordered Neural Circuits

A major challenge in neuroscience is reconciling idealized theoretical models with complex, heterogeneous experimental data. We address this challenge through the lens of continuous-attractor networks...

www.biorxiv.org

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Venki Murthy @neurovenki.bsky.social · Jan 27

Theory in neuroscience, you say? How about this preprint by @david-g-clark.bsky.social, with a couple of others you might recognize? :-) #neuroscience

Symmetries and continuous attractors in disordered neural circuits

A major challenge in neuroscience is reconciling idealized theoretical models with complex, heterogeneous experimental data. We address this challenge through the lens of continuous-attractor networks...

www.biorxiv.org

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Reposted by Cengiz Pehlevan

M Ganesh Kumar @mgkumar138.bsky.social · Dec 17

Our preprint with @frostedblakess.bsky.social, @jzv.bsky.social, @cpehlevan.bsky.social is out!

We develop a simple reinforcement learning model that recapitulates 3 disparate hippocampal dynamics. With ablation studies, these representations improve the speed and flexibility of policy learning.

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Reposted by Cengiz Pehlevan

Jacob Zavatone-Veth @jzv.bsky.social · Dec 16

The official ad for this postdoc position is now (finally) live, see academicpositions.harvard.edu/postings/14486!

Postdoctoral Fellow in Theoretical & Computational Neuroscience

Postdoctoral positions are available in Jacob Zavatone-Veth’s research group at Harvard's Center for Brain Science. We are broadly interested in the theory of neural computation; see jzv.io for more i...

academicpositions.harvard.edu

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