Explainable artificial intelligence for scientific discovery: trends and challenges | S. Scardapane скачать в хорошем качестве

Explainable artificial intelligence for scientific discovery: trends and challenges | S. Scardapane

Explainable artificial intelligence for scientific discovery: trends and challenges | S. Scardapane Speaker: Prof Simone Scardapane, Tenure-track assistant professor at Sapienza University of Rome Explainable AI is a set of tools and techniques to understand and debug neural network models. In this talk we will overview some of the most common approaches, ranging from input attribution (e.g., saliency maps) to data attribution and to the recent ideas of mechanistic interpretability. We will list open challenges and issues (e.g., polysemanticity), especially in contexts of scientific analysis and discovery in high-energy physics. We will close with ideas and trends for future research in the area. This talk is part of the Liverpool Virtual Seminar Series on Data Intensive Science; more information can be found at https://indico.ph.liv.ac.uk/e/data_sc... #data #bigdata #datascience #AI