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priesemann-group's Projects

bayesflow icon bayesflow

A library for constructing specialized neural networks for Bayesian parameter inference (invertible networks) and Bayesian model selection (evidential networks).

bn_coalescence_finite-size-scaling icon bn_coalescence_finite-size-scaling

Code used to generate 'Description of spreading dynamics by microscopic network models and macroscopic branching processes can differ due to coalescence' by Zierenberg et al.

bn_dynamic-range icon bn_dynamic-range

Characterize dynamic range of branching network (directed percolation) with and without coalescence

covid19_inference icon covid19_inference

Bayesian python toolbox for inference and forecast of the spread of the Coronavirus

dendritic_balance icon dendritic_balance

Code to reproduce experiments in "Local dendritic balance enables learning of efficient representations in networks of spiking neurons"

historydependence icon historydependence

Code to reproduce results in "Embedding optimization reveals long-lasting history dependence in neural spiking activity"

icomo icon icomo

Tools for the inference of compartmental models

mismatch_responses icon mismatch_responses

These files accompany the results obtained in "Visuomotor mismatch responses as a hallmark of explaining away in causal inference".

nninfo icon nninfo

A Python Package for the Analysis of Deep Neural Networks using Information Theory

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