Other topics which are covered in the course, but the corresponding chapters are not yet online and are to appear:
| Topic | Status |
|---|---|
| Surrogates | ✔️ Done |
| Neural networks with Flax | ✔️ Done |
| Bayesian neural networks | ⬜ To do |
| So, why Numpyro? | ⬜ To do |
| Variational inference | ⬜ To do |
| Introduction to deep generative models | ⬜ To do |
| Variational autoencoders (VAEs), normalising flows (NFs) | ⬜ To do |
| Deep generative surrogates and PriorCVAE | ⬜ To do |
| Simulation-based inference | ⬜ To do |
Further interesting topics which the course might not have time to cover (but I might add them to the online version in the future):
- Bayesian regularisation from optimisation perspective
- Laplace approximation
- Bayesian optimisation
- Active learning
- Renewal equation
- Hilbert Space Gaussian Process approximation (HSGP)