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M. U. Khalid

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Review Open access Aug 2026

A survey of theory-grounded interpretability for deep neural networks

This survey takes a complementary, theory-grounded perspective, examining interpretability through four classical machine learning (ML) frameworks, each grounded in a mature mathematical theory, and concludes with open problems and directions for scalable, theory-grounded interpretability.

M. U. Khalid, Abeer A. K. Alharbi, Shariq Bashir et al. · 0 citations

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