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mackelab.bsky.social
Machine Learning in Science
@mackelab.bsky.social
We build probabilistic #MachineLearning and #AI Tools for scientific discovery, especially in Neuroscience. Probably not posted by @jakhmack.bsky.social.

📍 @ml4science.bsky.social‬, Tübingen, Germany
Guy Moss (@gmoss13.bsky.social) developed and applied simulation-based inference methods to solve inference problems in glaciology, in collaboration with @geophys-tuebingen.bsky.social. E.g., openreview.net/forum?id=yB5... 3/3
January 13, 2026 at 3:43 PM
Julius Vetter (@vetterj.bsky.social) worked on deep generative modeling and simulation-based Bayesian inference, with applications to (physiological) time series data. E.g., openreview.net/forum?id=kN0... 2/3
January 13, 2026 at 3:43 PM
Happy 2026 everyone! Two freshly minted PhDs 🧑‍🎓emerged from our lab at the end of last year.
We congratulate Dr Julius Vetter (@vetterj.bsky.social) and Dr Guy Moss (@gmoss13.bsky.social)! Here seen celebrating with the lab 🎳. 1/3
January 13, 2026 at 3:43 PM
AutoSBI Poster: Tuesday 2 Dec 10:30am at the Amortized ProbML workshop, Copenhagen 11/11
December 1, 2025 at 4:16 PM
Fifth, we bring AutoML to SBI pipelines with a practical performance metric that does not require ground-truth posteriors, improving inference quality on the SBI benchmark! By @swagatam.bsky.social, @gmoss13.bsky.social, @keggensperger.bsky.social, @jakhmack.bsky.social 10/11
December 1, 2025 at 4:16 PM
Kalman filtering meets Jaxley poster #2015: Thu 4 Dec 11:00am at San Diego ➡️ openreview.net/forum?id=1si... 9/11
Identifying multi-compartment Hodgkin-Huxley models with...
Multi-compartment Hodgkin-Huxley models are biophysical models of how electrical signals propagate throughout a neuron, and they form the basis of our knowledge of neural computation at the...
openreview.net
December 1, 2025 at 4:16 PM
Fourth, in collaboration with Ian C Tanoh and Scott Linderman, we used the Jaxley toolbox and extended Kalman filters to estimate the marginal log-likelihood of a biophysical neuron model. We showed that this enables identifying biophysical parameters given extracellular recordings. 8/11
December 1, 2025 at 4:16 PM
Retina model with Jaxley poster #2015: Friday 5 Dec 11:00am at San Diego ➡️ openreview.net/forum?id=ayj... 7/11
A data and task-constrained mechanistic model of the mouse outer...
Visual processing starts in the outer retina where photoreceptors transform light into electrochemical signals. These signals are modulated by inhibition from horizontal cells and sent to the inner...
openreview.net
December 1, 2025 at 4:16 PM
Third, in collaboration with @kyrakadhim.bsky.social, @philipp.hertie.ai, and others, we built a task- and data-constrained biophysical network of the outer plexiform layer of the mouse retina. To optimize this model, we built it on top of our Jaxley toolbox for differentiable simulation. 6/11
December 1, 2025 at 4:16 PM
NPE-PFN poster #509: Thursday 4 Dec 11:00am at San Diego and Thursday 4 Dec 10:30am at Copenhagen ➡️ openreview.net/forum?id=kN0... 5/11
Effortless, Simulation-Efficient Bayesian Inference using Tabular...
Simulation-based inference (SBI) offers a flexible and general approach to performing Bayesian inference: In SBI, a neural network is trained on synthetic data simulated from a model and used to...
openreview.net
December 1, 2025 at 4:16 PM
Second, come by to check out NPE-PFN: We leverage the power of tabular foundation models for training-free and simulation-efficient SBI. SBI has never been so effortless! By @vetterj.bsky.social, Manuel Gloeckler, @danielged.bsky.social, @jakhmack.bsky.social 4/11
December 1, 2025 at 4:16 PM
FNOPE poster #601: Friday 5 Dec 4:30pm at San Diego and Thursday 4 Dec 10:30am at Copenhagen ➡️ openreview.net/forum?id=yB5... 3/11
FNOPE: Simulation-based inference on function spaces with Fourier...
Simulation-based inference (SBI) is an established approach for performing Bayesian inference on scientific simulators. SBI so far works best on low-dimensional parametric models. However, it is...
openreview.net
December 1, 2025 at 4:16 PM
First, we introduce FNOPE, a new simulation-based inference approach for efficiently and flexibly inferring function-valued parameters. By @gmoss13.bsky.social, @leahsmuhle.bsky.social, Reinhard Drews, @jakhmack.bsky.social and @coschroeder.bsky.social 2/11
December 1, 2025 at 4:16 PM
Our group is at NeurIPS and EurIPS this year with four papers and one workshop poster. If you are either curious about SBI with autoML, with foundation models, or on function spaces or about differentiable simulators with Jaxley, have a look below 👇 1/11
December 1, 2025 at 4:16 PM
Reposted by Machine Learning in Science
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)
FNOPE: Simulation-based inference on function spaces with Fourier...
Simulation-based inference (SBI) is an established approach for performing Bayesian inference on scientific simulators. SBI so far works best on low-dimensional parametric models. However, it is...
openreview.net
December 1, 2025 at 8:34 AM
We are looking for a Research Engineer (E13 TV-L) to work at the intersection of #ML and #compneuro! 🤖🧠

Help us build large-scale bio-inspired neural networks, write high-quality research code, and contribute to open-source tools like jaxley, sbi, and flyvis 🪰.

More info: www.mackelab.org/jobs/
Jobs - mackelab
The MackeLab is a research group at the Excellence Cluster Machine Learning at Tübingen University!
www.mackelab.org
November 28, 2025 at 1:54 PM
Check out our website for the whole team: www.mackelab.org/people/ 7/7
People - mackelab
The MackeLab is a research group at the Excellence Cluster Machine Learning at Tübingen University!
www.mackelab.org
November 28, 2025 at 10:26 AM
Maren joined the lab as PhD student in October to work on connectome-constrained models of neural activity and behavior in the fruit fly. She holds an MSc Computational Neuroscience from the BCCN Berlin. 6/7
November 28, 2025 at 10:26 AM
Byoungsoo (@byoungsookim.bsky.social) joined as a research scientist in October, upon finishing his Master's in Computational Neuroscience in the lab. He is working on modeling optomotor response circuits with a 3D compound eye model of the fruit fly. 5/7
November 28, 2025 at 10:26 AM
Isaac joined as a master’s thesis student working on representation learning for connectome-constrained models. Now, as a PhD student since July, he’s applying this to models of the fruitfly. He previously did an MSc at AIMS South Africa. 4/7
November 28, 2025 at 10:26 AM
Nicolas previously worked on computational neuroscience and NLP projects at EPFL. He joined the lab in June as a PhD student and is interested in building foundational models for neurophysiology data and applying LLMs for scientific discovery. 3/7
November 28, 2025 at 10:26 AM
Stefan (@stewah.bsky.social) joined the lab as a PhD student in June. He completed his Bachelor’s and Master’s degrees in Physics at Heidelberg University. He works on using LLMs to discover scientific models. 2/7
November 28, 2025 at 10:26 AM
MackeLab has grown! 🎉 Warm welcome to 5(!) brilliant and fun new PhD students / research scientists who joined our lab in the past year — we can’t wait to do great science and already have good times together! 🤖🧠 Meet them in the thread 👇 1/7
November 28, 2025 at 10:26 AM
Nicolas has previously worked on computational neuroscience and NLP projects at EPFL. He joined the lab in June as a PhD student and is currently interested in building foundational models for neurological data and applying LLMs for scientific discovery. 3/7
November 28, 2025 at 9:18 AM
Stefan (@stewah.bsky.social) joined the lab as a PhD student in June. He completed his Bachelor’s and Master’s degrees in Physics at Heidelberg University. At the moment, he is working on using LLMs to discover scientific models. 2/7
November 28, 2025 at 9:18 AM