default search action

combined dblp search
author search
venue search
publication search

ask others

"AI Explainability 360: An Extensible Toolkit for Understanding Data and ..."

Vijay Arya et al. (2020)

> Home

Details and statistics

DOI: —

access: open

type: Journal Article

metadata version: 2024-09-11

- view
  - electronic edition @ jmlr.org (open access)
- export record
  dblp key:
  - journals/jmlr/AryaBCDHHHLLMMP20
- ask others
- share record
  persistent URL:
  - https://dblp.org/rec/journals/jmlr/AryaBCDHHHLLMMP20
Vijay Arya, Rachel K. E. Bellamy, Pin-Yu Chen, Amit Dhurandhar, Michael Hind, Samuel C. Hoffman, Stephanie Houde, Q. Vera Liao, Ronny Luss, Aleksandra Mojsilovic, Sami Mourad, Pablo Pedemonte, Ramya Raghavendra, John T. Richards, Prasanna Sattigeri, Karthikeyan Shanmugam, Moninder Singh, Kush R. Varshney, Dennis Wei, Yunfeng Zhang:
AI Explainability 360: An Extensible Toolkit for Understanding Data and Machine Learning Models. J. Mach. Learn. Res. 21: 130:1-130:6 (2020)

manage site settings

To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.