Jan-Matthis Lueckmann
Research scientist at Google in Zurich
research.google/teams/connectomics
PhD from @mackelab.bsky.social
- Reposted by Jan-Matthis LueckmannSimulation-based inference (SBI) has transformed parameter inference across a wide range of domains. To help practitioners get started and make the most of these methods, we joined forces with researchers from many institutions and wrote a practical guide to SBI. 📄 Paper: arxiv.org/abs/2508.12939
- Reposted by Jan-Matthis LueckmannOur 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...
- Reposted by Jan-Matthis Lueckmann“Mapping ion channel function” doi.org/10.7554/eLif... isn’t exactly a citation slayer, but it’s still one of my favourites (& my first independent project). Today we push pt 2, where we trace code origin & unite almost all channel models in a common expression. Boom! www.biorxiv.org/content/10.1...
- Reposted by Jan-Matthis LueckmannNew 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! ⚡️
- Reposted by Jan-Matthis LueckmannWouldn't it be great if we could not only image large connectomic volumes but also completely reconstruct them? And if a whole mouse brain project didn't cost billions? With the PATHFINDER preprint (www.biorxiv.org/content/10.1...), we preview a future where it doesn't have to.
- We'll present our #ICLR2025 spotlight on ZAPBench this afternoon: 📍 Hall 3 #61!
- ⚡️ Excited to introduce ZAPBench, our #ICLR2025 spotlight: The Zebrafish Activity Prediction Benchmark measures progress in predicting neural activity within an entire vertebrate brain (70k+ neurons!) Explore interactive visualizations, datasets, code + paper: google-research.github.io/zapbench 🧠🧪
- ⚡️ Excited to introduce ZAPBench, our #ICLR2025 spotlight: The Zebrafish Activity Prediction Benchmark measures progress in predicting neural activity within an entire vertebrate brain (70k+ neurons!) Explore interactive visualizations, datasets, code + paper: google-research.github.io/zapbench 🧠🧪
- 🧠 How accurately can future neural activity be predicted from past activity at the scale of the whole brain? Larval zebrafish offer a unique opportunity to address this question, as they are currently the only vertebrate species in which whole-brain activity can be recorded at cellular resolution.
- 🔬 We collected and extensively processed a 4d dataset imaged with a lightsheet microscope. The resulting 3d movie covers over 70,000 neurons of a fish exposed to various visual stimuli.
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View full thread+ special shout-out to @alexbchen.bsky.social who recorded the activity dataset!
