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AstroStat School 2026 — Rome
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AstroStat School 2026 — Rome
Introduction to Classical Statistics
Hypothesis Testing
Maximum Likelihood Estimation
Introduction to Machine Learning and Clustering
Introduction to Bayesian Statistics
Applied Bayesian Statistics
Basics of Markov Chain Monte Carlo
Classification
Gaussian Processes
Time Series Analysis
Machine Learning Practices and Protocols
Introduction to Deep Learning and Regression Workshop
Optimization with Graphics Processing Units
Neural Network Explainability
Introduction to Simulation Based Inference
Simulation Based Inference: Exercises
Diffusion Models
Intro to AI Agents
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