A Python library for amortized Bayesian workflows using generative neural networks.

Uncertainpy: a Python toolbox for uncertainty quantification and sensitivity analysis, tailored towards computational neuroscience.

Teaching materials for BayesCog at Faculty of Psychology, University of Vienna

Workshop on basic machine learning, computational modeling, psychophysics, basic data analysis and experiment design

Simulation and optimization of neural circuits for MEG/EEG source estimates

Website for standards and governance of the Open Modeling Foundation

computational and brain/behavior modeling

Sensitivity analysis using simulation decomposition

LibHip: An Open-Access Hip Joint Model Repository suitable for Finite Element Method Simulation

Code and data for Zhang, Lengersdorff et al. (2020)

The computational modeling tool for custom atomistic model of calcium-silicate-hydrates (C-S-H)

A Python-based model simulating the behaviour of the slime mould using the geometric data of Nanjing subway system.

Laptime Simulation tool, special built for Formula SAE.

comses.net wagtail site

Code and data for Zhang & Gläscher (2020)

Teaching materials for BayesCog workshop, UKE Hamburg (Part 1).

Lumbar Model Generator

This script explicitly includes the parameters such as fiber length, diameter, orientation, distribution, and fiber volume fraction. Straight or curved/wavy fibers with random curvatures can be generated to closely approximate fiber morphology in the matrix.

Teaching materials for BayesCog workshop, UKE Hamburg (Part 2).

Original C++ version of emergent: originally hosted under svn at https://grey.colorado.edu/svn/emergent