Towards Higher-Order and Disentangled Explainable AI
Institute for Pure & Applied Mathematics (IPAM) via YouTube
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Explore advanced concepts in Explainable AI through this conference talk by Gregoire Montavon from Freie Universität Berlin. Delve into the evolution of explanation techniques, moving beyond first-order methods like LRP to more sophisticated approaches. Discover how to identify joint contributions of feature collections and decompose explanations into disentangled components. Gain insights into higher-order and disentangled explanations that enhance the expressiveness of AI interpretability methods. Understand the latest developments in making complex nonlinear machine learning models more transparent and interpretable.
Syllabus
Gregoire Montavon - Towards Higher-Order and Disentangled Explainable AI - IPAM at UCLA
Taught by
Institute for Pure & Applied Mathematics (IPAM)