One Explanation Does Not Fit All: A Toolkit And Taxonomy Of AI Explainability Techniques
- 2021
- INFORMS 2021
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135 results for Kush R. Varshney
Human Cognitive Biases in Interpreting Machine Learning
- Charvi Rastogi
- Yunfeng Zhang
- et al.
- 2020
- INFORMS 2020
Empirical and Theoretical Relationships Among Pillars of Trustworthy Machine Learning
- Kush R. Varshney
- Moninder Singh
- 2020
- INFORMS 2020
Automated Meta-Analysis in Medical Research: A Causal Learning Perspective
- Lu Cheng
- Dmitriy A. Katz-Rogozhnikov
- et al.
- 2021
- CHIL 2021
Socially responsible AI algorithms: Issues, purposes, and challenges
- Lu Cheng
- Kush R. Varshney
- et al.
- 2021
- JAIR
Decision making with quantized priors leads to discrimination
- Lav R. Varshney
- Kush R. Varshney
- 2017
- Proceedings of the IEEE
Targeting Villages for Rural Development Using Satellite Image Analysis
- Kush R. Varshney
- George H. Chen
- et al.
- 2015
- Big Data
Humble AI
- Bran Knowles
- Jason D'Cruz
- et al.
- 2023
- CACM
Human-centered explainability for life sciences, healthcare, and medical informatics
- Sanjoy Dey
- Prithwish Chakraborty
- et al.
- 2022
- Patterns
Deciding Fast and Slow: The Role of Cognitive Biases in AI-assisted Decision-making
- Charvi Rastogi
- Yunfeng Zhang
- et al.
- 2022
- PACM HCI