Uncertainpy: a Python toolbox for uncertainty quantification and sensitivity analysis, tailored towards computational neuroscience.
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Updated
Sep 28, 2022 - Python
Uncertainpy: a Python toolbox for uncertainty quantification and sensitivity analysis, tailored towards computational neuroscience.
Workshop on basic machine learning, computational modeling, psychophysics, basic data analysis and experiment design
Teaching materials for BayesCog at Faculty of Psychology, University of Vienna
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
Code and data for Zhang, Lengersdorff et al. (2020)
LibHip: An Open-Access Hip Joint Model Repository suitable for Finite Element Method Simulation
comses.net wagtail site
Laptime Simulation tool, special built for Formula SAE.
Teaching materials for BayesCog workshop, UKE Hamburg (Part 1).
Code and data for Zhang & Gläscher (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.
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
A FreeCAD-based Project Chrono Preprocessor for Various Models
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