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Debugging Tests for Model Explanations


Nov 10, 2020
Julius Adebayo, Michael Muelly, Ilaria Liccardi, Been Kim

* A shorter version of this work will appear at Neurips 2020 

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Assessing the (Un)Trustworthiness of Saliency Maps for Localizing Abnormalities in Medical Imaging


Aug 06, 2020
Nishanth Arun, Nathan Gaw, Praveer Singh, Ken Chang, Mehak Aggarwal, Bryan Chen, Katharina Hoebel, Sharut Gupta, Jay Patel, Mishka Gidwani, Julius Adebayo, Matthew D. Li, Jayashree Kalpathy-Cramer

* Submitted to Nature Machine Intelligence. First four authors contributed equally to this work 

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Explaining Explanations to Society


Jan 19, 2019
Leilani H. Gilpin, Cecilia Testart, Nathaniel Fruchter, Julius Adebayo

* NeurIPS 2018 Workshop on Ethical, Social and Governance Issues in AI 

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Sanity Checks for Saliency Maps


Oct 28, 2018
Julius Adebayo, Justin Gilmer, Michael Muelly, Ian Goodfellow, Moritz Hardt, Been Kim

* NIPS 2018 Camera Ready Version 

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Local Explanation Methods for Deep Neural Networks Lack Sensitivity to Parameter Values


Oct 08, 2018
Julius Adebayo, Justin Gilmer, Ian Goodfellow, Been Kim

* Workshop Track International Conference on Learning Representations (ICLR) 

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Investigating Human + Machine Complementarity for Recidivism Predictions


Aug 28, 2018
Sarah Tan, Julius Adebayo, Kori Inkpen, Ece Kamar


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The (Un)reliability of saliency methods


Nov 02, 2017
Pieter-Jan Kindermans, Sara Hooker, Julius Adebayo, Maximilian Alber, Kristof T. Schütt, Sven Dähne, Dumitru Erhan, Been Kim


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Iterative Orthogonal Feature Projection for Diagnosing Bias in Black-Box Models


Nov 15, 2016
Julius Adebayo, Lalana Kagal


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