Explainable Artificial Intelligence

Catalog description

Covers modern approaches to explaining the decision processes of deep neural networks. Includes major methods such as hidden states visualization; geometric, statistical, and information theoretic analysis of latent representations; CAM methods and sensitivity analysis; and locally interpretable models. Explores sources of bias and their remedies. Prerequisite: MTH 4320 or MTH 5320