A Python library for Automated Bayesian Inference in Dynamic Causal Modelling (DCM)
This repository contains Python code for efficient Bayesian Inference in DCM, including routines for Gradient-Descent and Markov Chain Monte Carlo schemes.
First install
conda env create -f environment.yml
conda activate abi-DCM
python -m ipykernel install --user --name abi-DCM
conda deactivate
git clone https://github.com/brainets/abi-DCM.git $HOME/abi-DCM
conda install conda-forge::jupyterlab
cd $HOME/abi-DCM/examples
jupyter-lab & \
(once JupyterLab opens up, choose abi-dcm as IPython kernel)
This research has been supported by EU’s Horizon 2020 Framework Programme for Research and Innovation under the Specific Grant Agreements No. 101147319 (EBRAINS 2.0 Project).
