I am at ICML and present our work on LLM-based model discovery with a probabilistic view. Let me know if you are around and want to chat! I'm happy to discuss ideas.

Machine Learning in Science@mackelab.bsky.social · 2mo ago

ModelSMC: we frame LLM-based scientific model discovery as Bayesian inference. Sequential Monte Carlo over executable model structures, with the LLM as a probabilistic proposal mechanism. 📍 Wed Jul 8, at 2:30–4:15 PM KST in Hall A #3512 📄 arxiv.org/abs/2602.18266 🧵 bsky.app/profile/mack...

Our work on training biophysical models with Jaxley is now out in @natmethods.nature.com. Led by @deismic.bsky.social, with @philipp.hertie.ai, @ppjgoncalves.bsky.social & @jakhmack.bsky.social et al. Paper: www.nature.com/articles/s41...

Jaxley: differentiable simulation enables large-scale training of detailed biophysical models of neural dynamics - Nature Methods

Jaxley is a versatile platform for biophysical modeling in neuroscience. It allows efficiently simulating large-scale biophysical models on CPUs, GPUs and TPUs. Model parameters can be optimized with ...

nature.com

Thrilled this is finally out! Heads off to @deismic.bsky.social and thanks for the amazing collaborative effort on this! Excited to see what people do with this :)

Michael Deistler@deismic.bsky.social · 10mo ago

I am super happy to share that our project on training biophysical models with Jaxley is now published in Nature Methods: www.nature.com/articles/s41...

At the European Retina Meeting and interested in biophysical modeling of the retina? Come stop by my poster (#081) tomorrow!

We spent a year writing this review of low-dim embeddings and arguing about things like epistemic roles and best practices :-) 20+ authors are all participants of the Dagstuhl seminar we held last year: www.dagstuhl.de/24122. Led by @alexandr.bsky.social and Cyril de Bodt. arxiv.org/abs/2508.15929

Looky Looky! 😍🥳👏 arxiv.org/abs/2508.12939 Super fun project, I ❤️ed coauthoring w/ @sbi-devs.bsky.social. Great lead by @deismic.bsky.social & @janboelts.bsky.social. Contribs by many talented people @jakhmack.bsky.social. 🙏 to #BenjaminKurtMiller for the kickstart! @helmholtzai.bsky.social

Simulation-Based Inference: A Practical Guide

A central challenge in many areas of science and engineering is to identify model parameters that are consistent with prior knowledge and empirical data. Bayesian inference offers a principled framewo...

arxiv.org

We are looking for an HPC Compute Cluster administrator to contribute to our ML Cloud! jobs.medizin.uni-tuebingen.de/Job/3574/HPC...

Ever wanted to do deep learning with a neural net that is one-to-one mapped to 65.05% of the fruit fly brain? 😄 Before this year ends, I will quickly advertise our code release of `flyvis.` Docs: t.ly/YqWzR Repo: t.ly/pMWpp Work with @jakhmack.bsky.social, @srinituraga.bsky.social and colleagues