From hackathon to release: sbi v0.25 is here! 🎉 What happens when dozens of SBI researchers and practitioners collaborate for a week? New inference methods, new documentation, lots of new embedding networks, a bridge to pyro and a bridge between flow matching and score-based methods 🤯 1/7 🧵

New preprint: SBI with foundation models! Tired of training or tuning your inference network, or waiting for your simulations to finish? Our method NPE-PF can help: It provides training-free simulation-based inference, achieving competitive performance with orders of magnitude fewer simulations! ⚡️

The neurons that encode sequential information into working memory do not fire in that same order during recall, a finding that is at odds with a long-standing theory. Read more in this month’s Null and Noteworthy. By @ldattaro.bsky.social #neuroskyence www.thetransmitter.org/null-and-not...

Many people in our lab use Scholar Inbox regularly -- highly recommended!

Thrilled to share that our paper on using simulation-based inference for inferring ice accumulation and melting rates for Antarctic ice shelves is now published in Journal of Glaciology! www.cambridge.org/core/journal...

Great news! Our March SBI hackathon in Tübingen was a huge success, with 40+ participants (30 onsite!). Expect significant updates soon: awesome new features & a revamped documentation you'll love! Huge thanks to our amazing SBI community! Release details coming soon. 🥁 🎉

🎓Hiring now! 🧠 Join us at the exciting intersection of ML and Neuroscience! #AI4science We’re looking for PhDs, Postdocs and Scientific Programmers that want to use deep learning to build, optimize and study mechanistic models of neural computations. Full details: www.mackelab.org/jobs/ 1/5

Excited to present our work on compositional SBI for time series at #ICLR2025 tomorrow! If you're interested in simulation-based inference for time series, come chat with Manuel Gloeckler or Shoji Toyota at Poster #420, Saturday 10:00–12:00 in Hall 3. 📰: arxiv.org/abs/2411.02728

Thanks so much for the shout-out, and congrats on your exciting work!! 🎉 🙂 Also, a good reminder to share that our work is now out in Cell Reports 🙏🎊 ⬇️ www.cell.com/cell-reports...

The @mackelab.bsky.social is represented at @cosynemeeting.bsky.social #cosyne2025 in Montreal with 3 posters, 2 workshop talks, and a main conference contributed talk (for the very first time in Mackelab history 🎉)!

Exciting new paper out of a Tübingen-Bonn collaboration, with three researchers from our cluster involved: first author @stefanieliebe.bsky.social, @matthijspals.bsky.social & @mackelab.bsky.social. Congrats to the team!

Science Alert 🚨: Our paper is now out in @natureneuro.bsky.social - We show that the firing phase of neurons in human MTL doesn’t reflect the order of events, challenging a long-standing theory of human memory. nature.com/articles/s41593-025-01893-7

Together with @dendritesgr.bsky.social, we’ll be hosting a tutorial on constructing and optimizing biophysical models (via Jaxley & DendroTweaks) 🚀 Join us in Florence if you like dendrites, biophysics, or optimization!

1) Some exciting science in turbulent times: How do mice distinguish self-generated vs. object-generated looming stimuli? Our new study combines VR and neural recordings from superior colliculus (SC) 🧠🐭 to explore this question. Check out our preprint doi.org/10.1101/2024... 🧵

Talk to @vetterj.bsky.social and @gmoss13.bsky.social about sourcerer at #Neurips2024 today! 📍Poster #4006 (East; 11 am PT)

1) With our @neuripsconf.bsky.social poster happening tomorrow, it's about time to introduce our Spotlight paper 🔦, co-lead with @jkapoor.bsky.social: Latent Diffusion for Neural Spiking data (LDNS), a latent variable model (LVM) which addresses 3 goals simultaneously:

How to find all fixed points in piece-wise linear recurrent neural networks (RNNs)? A short thread 🧵 
In RNNs with N units with ReLU(x-b) activations the phase space is partioned in 2^N regions by hyperplanes at x=b 1/7

Thrilled to announce we have three #NeurIPS2024 papers! Interested in simulating realistic neural data with diffusion models or recurrent neural networks, or in source distribution sorcery? Have a look 👇 1/4

Watching the sbi-toolbox grow up, seeing its many uses on a wide range of applications, and experiencing the growth, momentum + team-spirit of the sbi community has been amazing. We now have a short software paper with many new contributions and contributors! So many thanks, and get involved!

The sbi package is growing into a community project 🌍 To reflect this and the many algorithms, neural nets, and diagnostics that have been added since its initial release, we have written a new software paper 📝 Check it out, and reach out if you want to get involved: arxiv.org/abs/2411.17337

To introduce our science, let’s start with: we are hiring! Inspired to do a PhD or Postdoc in #AI4Science? Work with us on ML tools for scientific discovery. Full details: www.mackelab.org/jobs/ PhD students: Apply by Nov 15 (tomorrow!), directly to IMPRS-IS or ELLIS

Hi world! This is the brand-new BlueSky account of the Machine Learning in Science (@jakhmack.bsky.social) lab. We create probabilistic #MachineLearning and #AI Tools for scientific discovery — but more on that soon! For now let’s introduce ourselves with some pictures of our recent group retreat.