430 citations · 446 across the 7 of their papers we have counts for
Showing 2020Show all
2 papers · 1 filter
cs.LG2020★ 430 cited
Underspecification Presents Challenges for Credibility in Modern Machine Learning
Alexander D'Amour, Katherine Heller, Dan Moldovan +37
ML models often exhibit unexpectedly poor behavior when they are deployed in real-world domains. We identify underspecification as a key reason for these failures. An ML pipeline i…
eess.IV2020★ 3 cited
Quantitative and Qualitative Evaluation of Explainable Deep Learning Methods for Ophthalmic Diagnosis
Amitojdeep Singh, J. Jothi Balaji, Mohammed Abdul Rasheed +3
Background: The lack of explanations for the decisions made by algorithms such as deep learning has hampered their acceptance by the clinical community despite highly accurate resu…