Schedule

The following is a tentative schedule

Time	June 2 (Monday)	June 3 (Tuesday)	June 4 (Wednesday)	June 5 (Thursday)	June 6 (Friday)	June 9 (Monday)	June 10 (Tuesday)	June 11 (Wednesday)	June 12 (Thursday)	June 13 (Friday)
8:30	Registration
9:00	1. Preflight: 1. matrix operations; 2. Linear Regression (OLS) (80’)	Introduction to DL: 1. Preflight - calculus, chain rule; 2. Gradient Descent	Decision Trees XGBoost	Convolutional Neural Networks	Generative AI Likelihood-based Learning	Introduction to Transformers	Introduction to Vision Transformers	Introduction to Bayesian Methods	Bayesian Deep Learning	Bayesian Optimization
10:20	Coffee Break (30’)	Coffee Break	Coffee Break	Coffee Break	Coffee Break	Coffee Break	Coffee Break	Coffee Break	Coffee Break	Coffee Break
10:50	Linear Classifiers (Perceptron, Adaline) Historical approach (80’)	Optimizing Networks through GD: 1. GD, SGD, Mini-batch SGD; 2. Optimizers; 3. Regularization; 4. Schedulers	1. Pytorch Fundamentals; 2. Classification with Neural Networks (binary); 3. Multiclass approaches; 4. Implement binary classifier in pytorch (CMOD data)	Graph Neural Networks	Generative AI Towards Likelihood-free Learning	Intro to LLM (Jindong Wang)	Implementing a Basic Vision Transformer	Bayesian Regression Gaussian Process	Advanced Bayesian D (Hands On)	Bayesian Optimization
12:10	Lunch (80’)	Lunch	Lunch	Lunch	Lunch	Lunch	Lunch	Lunch	Lunch	Lunch
13:30	Getting setup with SW/HW (60’)	Tokamak Operations: Pegasus (Steffi Diem)	Tokamak Measurements (Eva Kostadinova)	Tokamak MHD stability: Disruption (Cristina Rea, Alex Saperstein)	Tokamak MHD stability: ELMs (Saskia Mordijck)	Collaborative research projects (Nick Murphy)	Tutorial MAST/MAST-U (Nathan Cummings)	Digilab: Equilibrium reconstruction uncertainty (Cyd Cowley)	Student Work Session	Group presentations
14:30	Coffee Break (30’)	Coffee Break	Coffee Break	Coffee Break	Coffee Break	Coffee Break	Coffee Break	Coffee Break	Coffee Break	Coffee Break
15:00	( 15:00-16:00 ) Short Tour ( 16:00-17:00) General introduction : Fusion and Magnetic Confinement (Saskia Mordijck)	( 15:00-16:00 ) Introduction to fusion dataset (Alex Saperstein) ( 16:00-17:00) Toy Regression Problem	Regression with PyTorch (CMOD data)	MNIST Classification GCN on MNIST Superpixels	Generative AI GlueX BCAL Example	Student Work Session	Student Work Session	Hands-on (digiLab)	Student Work Session	Group presentations
17:00	Welcome Reception		Al4Fusion Social					AI4Fusion Social		Closing remarks