Excited that our work on combining statistical field theory of neural networks with large-deviation theory is now published in @PhysRevLett (open access): https://t.co/8wyXHOekvH Was a great experience working on this with Tobias Kühn and Moritz Helias!

And the 2025 Onsager prize goes to …. Jean-Philippe Bouchaud, Leticia Cugliandolo, and Jorge Kurchan! Their works on out of equilibrium dynamics are so beautiful, influential and important - real gems. Huge congratulations !

Thrilled to share our new preprint on optimal replay protocols for continual learning using stat phys + control theory! Very excited about this direction 🚀

Very excited to announce openings for my first 2 lab members @chalmersuniv 1️⃣ PhD in theory of ML bias [ https://t.co/yLBlRRxazL] 2️⃣ Postdoc in ML theory [ https://t.co/mZWwDzUtS6] Beautiful campus, a liveable city near an archipelago 🛶 Work closely with me to shape the lab! 🌱

We got the cover at Cerebral Cortex! 🤩 The issue: https://t.co/kTSFhqR1p4 The paper: https://t.co/tY3flXM5Qw

Time for a tweeprint of our latest paper! We found that neuron densities follow a lognormal distribution within and across cerebral cortical areas in several species! 🧠🐒🐁🧍 🧵

Excited to announce RL at Harvard 2023, a one-day workshop on RL broadly construed. Date: August 29th, see https://t.co/M7UdQ0mTId for more. Submit your abstracts now! Hope you enjoy what @paul_masset, @jzavatoneveth, Kenneth Blum, @gershbrain, and I have put together!

Math in comp neuro summer camp!! Apply now!!! 10-28/July in lovely Norway (amazing/middle of nowhere). No tuition and room/board/food(good) is covered. Great experience/speakers/students/activities!!!! “fire together, wire together” Do it! https://t.co/uoQADQ1mfI

Today's the last day to apply for the CAJAL Machine Learning in Neuroscience summer school in beautiful Lisbon, Portugal. Please apply! https://t.co/aKsnxVV8ku Co-organizers: Gonzalo de Polavieja @dePolavieja & Memming Park @memming

We're going to be at #NeurIPS2022 with two papers: (1) one on the application of the mean-field theory in fitting spiking networks (SNNs) to neuronal recordings, and (2) another on a unifying framework for different models of memory storage. 1/3

🎉Applications are open for our #workshop on the theory of neural networks in Les Houches (France) from 20.-24.02.23, organised w/ @s_y_chung & @marc_mezard. Check out our fantastic set of speakers from neuro & ML and apply until Dec 1st https://t.co/OKtntMxTOS (and pls retweet!)

Our work on manifold geometric theory underlying fast learning of novel concepts led by Ben Sorcher of the Ganguli Lab is out. https://t.co/DfEJ5SXNE7 We apply our theory to object manifold representations in deep neural network (DNN) and in macaque IT cortex.

This implies that I managed to defend my PhD - super grateful for the support, input, and supervision by @sachavanalbada and Moritz Helias. It was a privilege (and a lot of fun) to work with the INM-6 team @fz_juelich.

A little late but I want to share that I started a fellowship under guidance of @HSompolinsky at the center for brain science @harvard. Excited to be part of the group and the CBS community!

Postdoc position in Sompolinsky Group: If you are interested in doing exciting postdoc research at Harvard at the forefront of computational neuroscience and the interface between natural and artificial intelligence, send application and 3 letters to hsompolinsky@mcb.harvard.edu

Bernstein conference continues! Since one poster was not enough come by today to poster III-2 at 12h45 This one is all about neuron densities in the cortex and why they are lognormal! 🧠🦠

a bit late but finally finished the COSYNE2022 blogpost. In it: 1. some works I found particularly interesting at the main conference 2. musings on "how to conference" 3. a report about our (best!) workshop on neural timescales with @roxana_zeraati https://t.co/FDrffgZXee

Please join us in the beautiful Norwegian fjords to learn about Computational Neuroscience. deadline for applications: 30 April 2022 https://t.co/irLwBbZDCW @adric_dunn @KISNeuro @FENSorg @KavliFoundation @NRSNeuro

Our Bayesian method for estimation of timescales (w/ @SelfOrgAnna and @EngelTatiana) is now out @NatComputSci, with exciting new additions to our initial preprint. Here is a 🧵

In a recent Article, @roxana_zeraati, @EngelTatiana and @SelfOrgAnna present a Bayesian method for unbiased estimation of timescales from different types of experimental data.

Don't forget to apply to the Cajal course in Computational Neuroscience! Deadline March 28!👇