Course Schedule

Monday, June 12:

8:45 – 9:00:         Welcome and Introduction
9:00 – 10:00:       Introduction to Machine Learning (Matthias Rupp)
10:00 – 10:20:     Coffee Break
10:20 – 11:20:     Kernel-based Regression (Matthias Rupp)
11:20 – 12:30:     Dimensional Reduction, Feature Selection, and Clustering techniques (Alex Rodriguez)
12:30 – 14:00:     Lunch Break
14:00 – 15:00:     Introduction to Neural Networks (Mark Tuckerman)
15:00 – 15:30:     Coffee Break
15:30 – 17:30:     Practical Session: Clustering with Feature Selection and Validation (Alex Rodriguez)

Tuesday, June 13:  

9:00 – 10:00:       Random Forests (Yingkai Zhang)
10:00 – 10:30:     Coffee break
10:30 – 11:30:     Learning Curves, Representations, and Training Sets I (Anatole von Lilienfeld)
11:30 – 12:30:     Learning Curves, Representations, and Training Sets II (Anatole von Lilienfeld)
12:30 – 14:00:     Lunch Break
14:00 – 15:00:     Review of Electronic Structure, Atomic, Molecular, and Crystal Representations (Mark Tuckerman)
15:00 – 15:30:     Coffee Break
15:30 – 17:30:     Practical Session: Learning Curves (Anatole von Lilienfeld)

Wednesday, June 14:

9:00 – 10:00:       Predicting Properties of Molecules and Materials (Matthias Rupp)
10:00 – 10:30:      Coffee Break
10:30 – 11:30:      Parameter Learning and Delta Learning (Anatole von Lilienfeld)
11:30 – 12:30:      Learning Electronic Densities (Mark Tuckerman)
                               ML Models of Crystal Properties (Anatole von Lilienfeld)
12:30 – 14:00:      Lunch Break
14:00 – 15:30:      Practical Session: Machine Learning and Property Prediction I (Matthias Rupp)
15:30 – 16:00:      Coffee Break
16:00 – 17:30:      Practical Session: Machine Learning and Property Prediction I (Matthias Rupp)

Thursday, June 15:  

9:00 – 10:00:        Machine Learning of Potential Energy Surfaces (Ming Chen)
10:00 – 10:30:      Coffee Break
10:30 – 11:30:      Machine Learning Based Enhanced Sampling (Ming Chen)
11:30 – 12:30:      Machine Learning of Free Energy Surfaces (Mark Tuckerman)
12:30 – 14:00:      Lunch Break
14:00 – 15:00:     Cluster-based Analysis of Molecular Simulations (Alex Rodriguez)
15:00 – 15:30:      Coffee Break
15:30 – 17:30:      Practical Session: Neural Network Learning of Free Energy Surfaces  (Mark Tuckerman)

Friday, June 16:

9:00 – 10:00:        Development of Protein-ligand Scoring Functions (Yingkai Zhang)
10:00 – 10:30:      Coffee Break
10:30 – 11:30:      Machine Learning in Structural Biology I (Yang Zhang)
11:30 – 12:30:      Machine Learning in Structural Biology II (Yang Zhang)
12:30 – 14:00:      Lunch Break
14:00 – 15:30:      Practical Session: Random Forests and Scoring Functions
(Yingkai Zhang)
15:30 – 16:00:      Coffee Break
16:00 – 17:30:      Practical Session: Machine Learning for Structural Bioinformatics  (Yang Zhang)