GrainLearning
GrainLearning is a Bayesian uncertainty quantification and propagation toolbox for simulations of granular materials. It is primarily used to infer and quantify parameter uncertainties in computational models from observation data (i.e. inverse analyses or data assimilation).
- Bayesian Inference
- Data assimilation
- Machine learning
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- Jupyter Notebook
- Python
- PureBasic
- + 1