Session 7

Process-based modelling & Machine Learning

Further reading and materials

Machine Learning

• Read: Deep learning and process-based modelling
• Read: Example of limitations
• Read: David MacKay, Information Theory, Inference, and Learning Algorithms

Useful R packages:

• BART package: Bayesian Additive Regression Trees”
• BASS package: Bayesian Adaptive Spline Surfaces
• BayesGPfit package: Bayesian Gaussian Process Regression Fitting package

Presentations

🖥️ Presentation 7a - Process-based models 🖥️ Presentation 7b - Machine learning

Practicals

• Practical 7a - Process-based models
• Practical 7b - Machine learning

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