American Psychological Association 6th edition

Purian, R., Katz, N., & Feldman, B. (2022). Explainability Using Bayesian Networks for Bias Detection: FAIRness with FDO. Research Ideas & Outcome Journal, 1-5. https://doi.org/10.3897/rio.8.e95953

ISO-690 (author-date, English)

PURIAN, Ronit, KATZ, Natan und FELDMAN, Batya, 2022. Explainability Using Bayesian Networks for Bias Detection: FAIRness with FDO. Research Ideas & Outcome Journal. 12 Oktober 2022. P. 1-5. DOI 10.3897/rio.8.e95953.

Modern Language Association 9th edition

Purian, R., N. Katz, und B. Feldman. „Explainability Using Bayesian Networks for Bias Detection: FAIRness With FDO.“. Research Ideas & Outcome Journal, Oktober 2022, S. 1-5, https://doi.org/10.3897/rio.8.e95953.

Mohr Siebeck - Recht (Deutsch - Österreich)

Purian, Ronit/Katz, Natan/Feldman, Batya: Explainability Using Bayesian Networks for Bias Detection: FAIRness with FDO., Research Ideas & Outcome Journal 2022, 1-5.

Emerald - Harvard

Purian, R., Katz, N. und Feldman, B. (2022), „Explainability Using Bayesian Networks for Bias Detection: FAIRness with FDO.“, Research Ideas & Outcome Journal, S. 1-5.

Achtung: Diese Zitate sind unter Umständen nicht zu 100% korrekt.