What Makes a Good KRI? Using FAIR to Discover Meaningful Metrics
Discover how to identify meaningful Key Risk Indicators using FAIR methodology. Learn characteristics of effective metrics and apply sensitivity analysis through case studies to improve risk governance.
Essentials of Math Modeling - Introduction to Regression and Statistical Ideas
Explore linear regression, data transformations, and statistical concepts in mathematical modeling. Learn MATLAB examples, sensitivity analysis, and problem-solving techniques for real-world applications.
Non-Profiled Deep Learning-Based Side-Channel Attacks with Sensitivity Analysis
Explore non-profiled deep learning techniques for side-channel attacks, focusing on sensitivity analysis to enhance attack effectiveness and efficiency in cryptographic systems.
Sensitivity and Interpretability of AI Models in Regulated Industries
Explore sensitivity analysis for AI model interpretability in regulated industries. Learn design and implementation approaches using case studies from healthcare and human activity data.
Introduction to Sensitivity Analysis - Week 12
Explore sensitivity analysis techniques to assess how changes in input variables affect model outcomes and decision-making processes.
The Personalisation of Cardiovascular Models Using Julia
Innovative workflow for personalizing cardiovascular models using Julia, combining data assimilation, sensitivity analysis, and optimization to enhance clinical decision-making and improve patient outcomes.
Trade-off Between Optimality and Explainability in Machine Learning Models
Explore the trade-off between model explainability and accuracy in AI/ML, focusing on counterfactual explainability and optimization challenges in high-risk applications.