Measuring the Uncertainty of Environmental Good Preferences with Bayesian Deep Learning-Reference-Cited by-同舟云学术

Measuring the Uncertainty of Environmental Good Preferences with Bayesian Deep Learning

Published:2022-09-07 Issue: Volume: Page:
ISSN:
Container-title:Conference on Information Technology for Social Good
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Author:

Flores Ricardo¹,Tlachac ML²,Rundensteiner Elke A.³

Affiliation:

1. Data Science, Worcester Polytechnic Institute, United States

2. Bryant University, USA

3. Data Science, Computer Science, Worcester Polytechnic Institute, USA

Publisher

ACM

Reference44 articles.

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2. Kenneth Arrow , Robert Solow , Paul R Portney , 1993. Report of the NOAA panel on contingent valuation. Federal register 58, 10 ( 1993 ), 4601–14. Kenneth Arrow, Robert Solow, Paul R Portney, 1993. Report of the NOAA panel on contingent valuation. Federal register 58, 10 (1993), 4601–14.

3. Kenneth J Arrow . 2001. Valuing environmental preferences: theory and practice of the contingent valuation method in the US , EU, and developing countries . Oxford University Press on Demand. Kenneth J Arrow. 2001. Valuing environmental preferences: theory and practice of the contingent valuation method in the US, EU, and developing countries. Oxford University Press on Demand.

4. Xiao Bai Xiang Wang Xianglong Liu Qiang Liu Jingkuan Song Nicu Sebe and Been Kim. 2021. Explainable deep learning for efficient and robust pattern recognition: A survey of recent developments. Pattern Recognition 120(2021). Xiao Bai Xiang Wang Xianglong Liu Qiang Liu Jingkuan Song Nicu Sebe and Been Kim. 2021. Explainable deep learning for efficient and robust pattern recognition: A survey of recent developments. Pattern Recognition 120(2021).

5. Combining socio-acoustic and contingent valuation surveys to value noise reduction