Fast and Easy Whole-Brain Network Model Parameter Estimation with Automatic Differentiation
by Marius Pille, Leon Martin, Emilius Richter, Dionysios Perdikis, Michael Schirner, Petra Ritter
Year:
2025
Publication:
bioRxiv
Abstract:
We present TVB-Optim, an open-source Python library providing a general and extensible framework for gradient-based optimization of brain network models build on JAX.
Link:
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Brief introduction of the dida co-author(s) and relevance for dida's ML developments.
Emilius Richter
During his studies of physics (FU Berlin) Emil developed his passion for machine learning, computational neuroscience and medical engineering. In his master thesis at Charité Berlin, he developed Bayesian Inference methods for whole-brain models and simulations. At dida he supports the sales team in the acquisition of new ML projects and strategic research collaborations.