SciML Notebooks

Interactive scientific machine learning demonstrations. Developed by James Kermode to support teaching of Scientific Machine Learning (ES98E) and Predictive Modelling and Uncertainty Quantification (PX914) in the HetSys CDT and Predictive Modelling and Scientific Computing MSc.

Probability DistributionsWASMmolab
Basis Function ExplorerWASMmolab
Bayesian Regression and UQWASMmolab
Kernel ExplorerWASMmolab
Sequential Bayesian Linear RegressionWASMmolab
GP RegressionWASMmolab
GP with Derivative ObservationsLIVEmolab
Bayesian OptimisationLIVEmolab
MLP RegressionLIVEmolab
BNN Regression (Variational Inference)LIVEmolab
Neural ODE SolverLIVEmolab
K-Means and GMM ClusteringWASMmolab
PCA ExplorerWASMmolab
PCA as an EM AlgorithmWASMmolab
Normalising FlowsLIVEmolab
Uncertainty in Models and Data: Reaction KineticsDEMOmolab

Student Dashboard STUDENT

Formgrader STAFF

WASM notebooks run in your browser (no login required). LIVE notebooks require University of Warwick SSO. DEMO presentations are public (no login required).

molab links open notebooks in marimo's free cloud environment — no login or installation required. Useful for external collaborators and students without a Warwick account.