This is a great opportunity to work at the intersection of ML and Biogeoscience! Based within the outstanding research community of Tübingen. Reach out if you are interested!

Machine Learning in Science@mackelab.bsky.social · 4mo ago

Come and work with us! We have a PostDoc position at the intersection of ML and Biogeoscience within the TERRA excellence cluster @terra-cluster.org, w/ Senckenberg. Be part of a great ML and Geo community and use ML to investigate fire and its impact on global vegetation🔥 🌱🌳 www.mackelab.org/jobs/

On the way to #EurIPS in Copenhagen. If you want to talk about SBI, ML for science or just have a chat you can find me at our poster. Or just send me a DM!

Guy Moss@gmoss13.bsky.social · 8mo ago

I’m super excited to present our new work in #Eurips2025 and #Neurips2025! We developed FNOPE: a new simulation-based inference (SBI) method which excels at inferring function-valued parameters! Paper: openreview.net/forum?id=yB5... Code: github.com/mackelab/fnope (1/9)

Simulation-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

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

velotest: finally on bioRxiv! check out our work on faithfulness of RNA velocity embeddings and apply it to your own data: github.com/mackelab/vel... work lead by @sbischoff.bsky.social

bioRxiv Bioinfo@biorxiv-bioinfo.bsky.social · 9mo ago

velotest: Statistical assessment of RNA velocity embeddings reveals quality differences for reliable trajectory visualizations https://www.biorxiv.org/content/10.1101/2025.10.26.683064v1

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 🧵

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

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! ⚡️

We're super happy: Our Cluster of Excellence will continue to receive funding from the German Research Foundation @dfg.de ! Here’s to 7 more years of exciting research at the intersection of #machinelearning and science! Find out more: uni-tuebingen.de/en/research/... #ExcellenceStrategy

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. 🥁 🎉

Happy to see this finally out! My collaboration with @pirta-palola.bsky.social started at the ProbAI summer school in Trondheim and is a great example what can happen if you meet smart people with different backgrounds and spend a whole week together discussing science, coding and having fun!

Pirta Palola@pirta-palola.bsky.social · last yr.

Happy to share that my second PhD chapter has been published: royalsocietypublishing.org/doi/10.1098/... Thank you to all my co-authors! @coschroeder.bsky.social @ymalhi.bsky.social @oxfordgeography.bsky.social @plymouthmarine.bsky.social @tuebingen-ai.bsky.social @noc.ac.uk @ephe-psl.bsky.social

🥳Great news, our JOSS paper "sbi reloaded" has been accepted! 🎉 This community lead by the fine folks of @sbi-devs.bsky.social is very welcoming and super fun to work with! I learn with every discussion I have. paper: joss.theoj.org/papers/10.21... review: github.com/openjournals...

[REVIEW]: sbi reloaded: a toolkit for simulation-based inference workflows · Issue #7754 · openjournals/joss-reviews

Submitting author: @janfb (Jan Boelts) Repository: https://github.com/sbi-dev/sbi Branch with paper.md (empty if default branch): joss-submission-2024 Version: v0.24.0 Editor: @boisgera Reviewers: ...

github.com