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David Adkins
David Adkins
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Method cards for prescriptive machine-learning transparency
D Adkins, B Alsallakh, A Cheema, N Kokhlikyan, E McReynolds, P Mishra, ...
Proceedings of the 1st International Conference on AI Engineering: Software …, 2022
132022
Prescriptive and descriptive approaches to machine-learning transparency
D Adkins, B Alsallakh, A Cheema, N Kokhlikyan, E McReynolds, P Mishra, ...
CHI conference on human factors in computing systems extended abstracts, 1-9, 2022
122022
Debugging the internals of convolutional networks
B Alsallakh, N Kokhlikyan, V Miglani, S Muttepawar, E Wang, S Zhang, ...
eXplainable AI approaches for debugging and diagnosis., 2021
112021
Are Convolutional Networks Inherently Foveated?
B Alsallakh, V Miglani, N Kokhlikyan, D Adkins, O Reblitz-Richardson
SVRHM 2021 Workshop@ NeurIPS, 2021
32021
Bias Mitigation Framework for Intersectional Subgroups in Neural Networks
N Kokhlikyan, B Alsallakh, F Wang, V Miglani, OA Yang, D Adkins
arXiv preprint arXiv:2212.13014, 2022
12022
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Artikkelit 1–5