Explainable AI

Published

Friday, December 20, 2024

Lecture 5 — Explainable AI in practice

How to properly incorporate explanations in machine learning projects and what aspects should you keep in mind? Over the past few years the need to explain the output of…

Tuesday, March 28, 2023

4 Counterfactual Explanations - Explaining and Debugging

How to explain a machine learning model such that the explanation is truthful to the model and yet interpretable to people? This question is key to ML explanations research…

Thursday, March 23, 2023

3 Explaining Deep Neural Network Models

Rigorously understanding how Deep Learning models function may allow us to steer and control their behavior and avoid unwanted consequences. In addition, today’s highly…

Sunday, March 19, 2023

2 Local Explanations - Concept and Methods

Machine learning models can be analyzed at a high level using global explanations, such as linear model coefficients. However, there are several limitations to these global…

Monday, March 13, 2023

Introduction to XAI

In this introduction lecture on explainability in AI, we will delve into the key topics that surround this emerging field. We will first provide an overview of the…

Sunday, March 5, 2023