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Machine Learning in Science

@mackelab

We build probabilistic #MachineLearning and #AI Tools for scientific discovery, especially in Neuroscience. Probably not tweeted by @jakhmack.
Tübingen mackelab.org Joined November 2017
172 Following 2.1K Followers 275 Posts

Latest posts 5

Machine Learning in Science @mackelab
Our work on training biophysical models with Jaxley is now out in @naturemethods. Led by @deismic_, with Philipp Berens, Pedro Gonçalves & @jakhmack et al.
nature.com/articles/s4159…
www.nature.com Jaxley: differentiable simulation enables large-scale training of detailed biophysical models of... 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...
Machine Learning in Science @mackelab
Talk to @guymoss13 and Julius Vetter about sourcerer at #Neurips2024 today!
📍Poster #4006 (East; 11 am PT)
Guy Moss @guymoss13 Dec 10, 2024
Julius Vetter (on Bluesky) and I are excited to present our work at #Neurips2024! We present Sourcerer: a maximum-entropy, sample-based solution to source distribution estimation.

Paper: openreview.net/forum?id=0cgDD…
Code: github.com/mackelab/sourc…
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Machine Learning in Science @mackelab
Welcome Daniel (@danigedon) to our lab!

In his PhD he focussed on time series and low-dimensional representations, and now he will work on model discovery for time series.

Outside the lab he's active from biking, to hiking or yoga-ing. Glad to have you join!
Daniel Gedon @danigedon Aug 8, 2024
Recently I defended my PhD thesis 🤓

While my face barely hides my thoughts on some questions, we had a blast celebrating later 🥳🎉

Now I am enjoying Swedish summer ☀️🇸🇪 and in September, I will join @mackelab at @uni_tue as PostDoc to continue with more fun research! 🇩🇪
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