Lectures
Week 1: Uncertainty and Modelling
Week 2: Gaussian Distributions to Processes
Week 3: Covariance Functions and Hyperparameter Optimization
Week 4: Optimizing Parameters
Week 5: Multi-output Gaussian Processes
Week 6: Approximate Gaussian Processes
Week 7: Non Gaussian Likelihoods
Week 8: Unsupervised Learning with Gaussian Processes
Week 9: Latent Force Models
Week 10: Bayesian Learning of GP-LVM
Week 11: Deep Gaussian Processes I
Week 12: Deep Gaussian Processes II
Week 13: Emulation
2021-09-15