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Program
Workshops
- Advances in Approximate Inference with GPs (Thursday, September 14)
Room: PLB-DS05, Pam Liversidge Building
Full Schedule
Day 1 September 11 (Monday)
Summer school
8:00-9:00 Arrivals
9:00-10:30 Introduction to GPs
[slides]
10:30-11:00 Coffee Break
11:00-12:30 A second introduction to GPs
[slides]
12:30-13:45 Lunch
13:45-15:30 Lab Session 1
15:30-16:00 Tea Break
16:00-17:00 Kernel Design
[slides]
Day 2 September 12 (Tuesday)
Summer school
8:00-9:00 Arrivals
9:00-10:30 Multi Output Gaussian Processes
[slides]
10:30-11:00 Coffee Break
11:00-12:30 Unsupervised Learning with GPs
[slides]
12:30-13:45 Lunch
13:45-15:30 Lab Session 2
15:30-16:00 Tea Break
16:00-17:00 Stochastic (partial) differential equations and Gaussian processes
[slides]
Day 3 September 13 (Wednesday)
Summer school
8:00-9:00 Arrivals
9:00-10:30 Introduction to Bayesian Optimization
[slides]
10:30-11:00 Coffee Break
11:00-12:30 Sparse Gaussian Process Approximations
[slides]
12:30-13:45 Lunch
13:45-15:30 Lab Session 3 - Bayesian optimization with GPyOpt
15:30-16:00 Tea Break
16:00-17:00 Integration over hyperparameters and estimation of predictive performance
[slides]
Day 4 September 14 (Thursday)
8:00-9:00 Arrivals
9:00-17:00 Advances in Approximate Inference with GPs