💬 AI for Good Webinar Series 'From Molecules to Models' - today with @arthurgretton.bsky.social (@ucl.ac.uk, ELLIS Fellow) on causal effect estimation. 📅 Oct 29th 🕓 17:00-18:00 CET 🔗 Registration: aiforgood.itu.int/event/learn-... ℹ️ More info: ellis.eu/news/continu...

⏰ Deadline approaching for our PhD programmes! 👋 Apply by 3 Nov to join us and immerse yourself in world-class research and vibrant London life! Gatsby Unit: ucl.ac.uk/life-science... @sainsburywellcome.bsky.social: sainsburywellcome.org/web/content/... Joint: www.ucl.ac.uk/life-science...

Looking forward to next week's Winter School on Causality and Explainable AI! xai-winter-school.github.io

Applying to the #ELLISPhD Program? If you are selecting a Gatsby Unit faculty member as your main supervisor, don't forget to apply to the Gatsby Unit PhD Programme in parallel. Our deadline is 3 Nov 2025. 👉 www.ucl.ac.uk/life-science...

Congratulations to all the new SWC & @gatsbyucl.bsky.social PhD students for successfully completing Boot Camp! We are delighted to welcome you to the community. Students showcased their robots in our hotly anticipated annual @noblackboxes.bsky.social Robot Competition 🦾⚽💻

🙋Are you interested in bridging theory & experiments? Applications are now open for 2026 entry to the Gatsby Unit & SWC joint PhD programme. Join us and be part of a vibrant research community! 💰 Fully-funded 4-year programme ℹ️ www.ucl.ac.uk/life-science... @sainsburywellcome.bsky.social

Interested in a #PhD in machine learning & theoretical neuroscience? Applications for 2026 entry to the Gatsby Unit PhD programme are open! 💰 Fully-funded 4-year programme 🤝 Close links to @sainsburywellcome.bsky.social ℹ️ www.ucl.ac.uk/life-sciences/gatsby/study-and-work/gatsby-unit-phd-programme

A complete brain-wide activity map at single-cell resolution has been revealed for the first time. Researchers recorded from 650,000+ neurons across 279 brain areas to track decision-making in mice. Read the story: 🔗 www.sainsburywellcome.org/web/research...

Made possible only by the unique environment and amazing community at Janelia and the Gatsby. @hhmijanelia.bsky.social @gatsbyucl.bsky.social Feedback, ideas, or requests for transgenic lines, protocols, and code are warmly welcome!

ProbNum 2025 Keynote 2 ``Gradient Flows on the Maximum Mean Discrepancy'' by @arthurgretton.bsky.social ( @gatsbyucl.bsky.social and Google DeepMind. Slides available here: probnum25.github.io/keynotes

📢 ❗JOB OPPORTUNITY: Today is the closing date for this fantastic role we are funding at @gatsbyucl.bsky.social. ⏰ Apply before 23.59BST. 👇

Aeon is a new platform for continuous brain and behaviour research in naturalistic environments — already used in 15+ projects, including long-term social learning studies. 🔗 www.sainsburywellcome.org/web/blog/new... 📄 Preprint: www.biorxiv.org/content/10.1...

Are similar representations in neural nets evidence of shared computation? In new theory work w/ Lukas Braun (lukasbraun.com) & @saxelab.bsky.social, we prove that representational comparisons are ill-posed in general, unless networks are efficient. @icmlconf.bsky.social @cogcompneuro.bsky.social

Main takeaway: Valid representational comparison relies on implicit assumptions (task-optimization *plus* efficient implementation). ⚠️ More work to do on making these assumptions explicit! 🧠 CCN poster (today): 2025.ccneuro.org/poster/?id=w... 📄 ICML paper (July): icml.cc/virtual/2025/poster/44890

Our #CCN2025 GAC debate w/ @gretatuckute.bsky.social, Gemma Roig (www.cvai.cs.uni-frankfurt.de), Jacqueline Gottlieb (gottlieblab.com), Klaus Oberauer, @mschrimpf.bsky.social &‬ @brittawestner.bsky.social asks: 📊 What benchmarks are useful for cognitive science? 💭 2025.ccneuro.org/gac

Sequential kernel embedding for mediated and time-varying dose response curves Appearing in Bernoulli: projecteuclid.org/journals/ber... with preprint here: arxiv.org/abs/2111.03950 ...along with code! github.com/liyuan9988/K... Rahul Singh, Liyuan Xu

JOB: We're recruiting for a 2-year post doc fellowship based at @gatsbyucl.bsky.social working with Prof Arthur Gretton to create new statistically efficient causal and interaction models with the aim of elucidating cellular interactions ⏰closing 27 August 👉 details: www.ucl.ac.uk/work-at-ucl/...

Does the brain learn by gradient descent? It's a pleasure to share our paper at @cp-cell.bsky.social, showing how mice learning over long timescales display key hallmarks of gradient descent (GD). The culmination of my PhD supervised by @laklab.bsky.social, @saxelab.bsky.social and Rafal Bogacz!

New from @sainsburywellcome.bsky.social, @gatsbyucl.bsky.social, NeuroGEARS & DataJoint: Aeon - an open-source platform combining long-term neural recording with naturalistic behavioural tracking in enriched habitats. 📑 Preprint: www.biorxiv.org/content/10.1...

🎓Thrilled to share I’ve officially defended my PhD!🥳 At @gatsbyucl.bsky.social, my research explored how prior knowledge shapes neural representations. I’m deeply grateful to my mentors, @saxelab.bsky.social and @caswell.bsky.social, my incredible collaborators, and everyone who supported me!

🥳 Congratulations to Rodrigo Carrasco-Davison on passing his PhD viva with minor corrections! 🎉 📜 Principles of Optimal Learning Control in Biological and Artificial Agents.

Come chat about this at the poster @icmlconf.bsky.social, 11:00-13:30 on Wednesday in the West Exhibition Hall #W-902!

Excited to share new work @icmlconf.bsky.social by Loek van Rossem exploring the development of computational algorithms in recurrent neural networks. Hear it live tomorrow, Oral 1D, Tues 15 Jul West Exhibition Hall C: icml.cc/virtual/2025... Paper: openreview.net/forum?id=3go... (1/11)

Distributional diffusion models with scoring rules at #icml25 Fewer, larger denoising steps using distributional losses! Wednesday 11am poster E-1910 arxiv.org/pdf/2502.02483 @vdebortoli.bsky.social Galashov Guntupalli Zhou @sirbayes.bsky.social @arnauddoucet.bsky.social

Accelerated Diffusion Models via Speculative Sampling, at #icml25 ! 16:30 Tuesday July 15 poster E-3012 arxiv.org/abs/2501.05370 @vdebortoli.bsky.social Galashov @arnauddoucet.bsky.social

👋 Attending #ICML2025 next week? Don't forget to check out work involving our researchers!

🎊 Congratulations to Kevin Huang (@kevhhuang.bsky.social‬) on passing his PhD viva with minor corrections! 🥳 🔖 Universality beyond the classical asymptotic regime

It was a pleasure to welcome work experience students to SWC and @gatsbyucl.bsky.social this week, through the Camden STEAM initiative with @ucllifesciences.bsky.social They explored our labs and learned about the many paths into #neuroscience www.sainsburywellcome.org/web/content/...

How do task dynamics impact learning in networks with internal dynamics? Excited to share our ICML Oral paper on learning dynamics in linear RNNs! with @clementinedomine.bsky.social @mpshanahan.bsky.social and Pedro Mediano openreview.net/forum?id=KGO...

🥳 Congratulations to Clementine Domine (@clementinedomine.bsky.social) on passing her PhD viva with minor corrections! 🎉 🔖 Balancing Learning Regimes: The Impact of Prior Knowledge on the Dynamics of Neural Representations

Dimitri Meunier, Antoine Moulin, Jakub Wornbard, Vladimir R. Kostic, Arthur Gretton Demystifying Spectral Feature Learning for Instrumental Variable Regression https://arxiv.org/abs/2506.10899

New research shows long-term learning is shaped by dopamine signals that act as partial reward prediction errors. The study in mice reveals how early behavioural biases predict individual learning trajectories. Find out more ⬇️ www.sainsburywellcome.org/web/blog/lon...

Our #Artist-in-Residence, Mary Yacoob, has produced new large-scale #cyanotype prints reimagining of #scientific visual data from @ucllifesciences.bsky.social #researchers. Faculty private #exhibition details here: tinyurl.com/YacoobUCL #artandscience #art #artwork @ucl.ac.uk @ucl-cdb.bsky.social

Last but not least of my travel updates: Courtesy of the very kind @slchau.bsky.social, I'm giving a talk at 14:30, 27 Jun @NTU CCDS in SG on data augmentation & Gaussian universality, which strings together several works over my PhD. If you're in SG/Lyon over the next few weeks, let me know! :)

Meanwhile, excited to be in #Lyon for #COLT2025, with a co-first author paper (arxiv.org/abs/2502.15752) with the amazing team -- Matthew M Mallory and our advisor Morgane Austern! Keywords: Gaussian universality, dependent data, convex Gaussian min-max theorem, data augmentation!

Sadly missing ICML due to visa :'(, but looking forward to share our ICML paper (arxiv.org/abs/2502.05318) as a poster at #BayesComp, Singapore! Work on symmetrising neural nets for schrodinger equation in crystals, with the amazing Zhan Ni, Elif Ertekin, Peter Orbanz and Ryan P. Adams

Composite Goodness-of-fit Tests with Kernels, now out in JMLR! www.jmlr.org/papers/v26/2... Test if your distribution comes from ✨any✨ member of a parametric family. Comes in MMD and KSD flavours, and with code. @oscarkey.bsky.social @fxbriol.bsky.social Tamara Fernandez

We’ve successfully automated part of the (neuro)scientific process. Now I may be out of a job. After a lot of iterations, here’s our framework for automatic discovery, built to embrace degeneracy and the realities of underconstrained modeling.

How does in-context learning emerge in attention models during gradient descent training? Sharing our new Spotlight paper @icmlconf.bsky.social: Training Dynamics of In-Context Learning in Linear Attention arxiv.org/abs/2501.16265 Led by Yedi Zhang with @aaditya6284.bsky.social and Peter Latham

Dimitri Meunier, Zikai Shen, Mattes Mollenhauer, Arthur Gretton, Zhu Li Optimal Rates for Vector-Valued Spectral Regularization Learning Algorithms https://arxiv.org/abs/2405.14778

🚨 New paper accepted at SIMODS! 🚨 “Nonlinear Meta-learning Can Guarantee Faster Rates” arxiv.org/abs/2307.10870 When does meta learning work? Spoiler: generalise to new tasks by overfitting on your training tasks! Here is why: 🧵👇

Our paper just came out in PRX! Congrats to Nishil Patel and the rest of the team* TL;DR: We analyse policy learning through the lens of statphys, revealing distinct scaling regimes with sharp transitions. 🔗 journals.aps.org/prx/abstract... *Seb Lee @sebgoldt.bsky.social @saxelab.bsky.social

Mattes Mollenhauer, Nicole M\"ucke, Dimitri Meunier, Arthur Gretton: Regularized least squares learning with heavy-tailed noise is minimax optimal https://arxiv.org/abs/2505.14214 https://arxiv.org/pdf/2505.14214 https://arxiv.org/html/2505.14214

SWC researchers reveal a new way that the brain learns. The second learning system is frequency-based and may explain how the brain forms habits and why they are so hard to break. Full story: www.sainsburywellcome.org/web/research...

Our paper "Solve Layerwise Linear Models First to Understand Neural Dynamical Phenomena" has been accepted as a position paper to ICML 2025! arxiv.org/abs/2502.21009 These models offer a tractable path to understanding complex neural dynamics—before diving into full nonlinearity. 1/4

Credal Two-Sample Tests of Epistemic Uncertainty at #AISTATS25 Compare credal sets: convex sets of prob measures where elements capture aleatoric uncertainty; set represents epistemic uncertainty. arxiv.org/abs/2410.12921 @slchau.bsky.social Schrab @sejdino.bsky.social @krikamol.bsky.social

Kernel Single Proxy Control for Deterministic Confounding at #AISTATS25 Proxy causal learning generally requires two proxy variables - a treatment and an outcome proxy. When is it possible to use just one? arxiv.org/abs/2308.04585 Liyuan Xu

Spectral Representation for Causal Estimation with Hidden Confounders at #AISTATS2025 A spectral method for causal effect estimation with hidden confounders, for instrumental variable and proxy causal learning arxiv.org/abs/2407.10448 Haotian Sun, @antoine-mln.bsky.social, Tongzheng Ren, Bo Dai

Density Ratio-based Proxy Causal Learning Without Density Ratios 🤔 at #AISTATS2025 An alternative bridge function for proxy causal learning with hidden confounders. arxiv.org/abs/2503.08371 Bozkurt, Deaner, @dimitrimeunier.bsky.social, Xu

📢 We have an opportunity for students to join our PhD programme in Theoretical Neuroscience and Machine Learning this September. Application deadline is 27 May 2025. Information & how to apply: www.ucl.ac.uk/gatsby/study-and-work/gatsby-unit-phd-programme