ICB Seminar


From data to mechanisms, and back

Prof. Jakob Macke; Professorship for Computational Neuroengineering TUM Department of Electrical and Computer Engineering
ICB Seminar room 121 at 11:30

Many fields of science make extensive use of complex simulations describing the structure and dynamics of the process being investigated. These models are  derived from knowledge of the underlying mechanisms and principles, and are of critical importance for scientific hypothesis-building. However, linking such complex models to high-dimensional empirical measurements can be challenging.  

We develop computational tools which aim to bridge the gap between data-driven machine learning and theory-driven, mechanistic modelling. In this talk, I will focus on our recent work on using neural conditional density estimators to perform Bayesian inference on simulation-based models. I will demonstrate the efficiency and flexibility of this approach, and highlight applications to dynamical models of biological systems and source-reconstruction in biological imaging.

Click here for additional information about Computational Neuroengineering

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