Measuring the Uncertainty of Environmental Good Preferences with Bayesian Deep Learning

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.

1. Francisco Alpizar Fredrik Carlsson Peter Martinsson 2001. Using choice experiments for non-market valuation. Working papers in economics/Göteborg University Dept. of Economics; no. 52 (2001). Francisco Alpizar Fredrik Carlsson Peter Martinsson 2001. Using choice experiments for non-market valuation. Working papers in economics/Göteborg University Dept. of Economics; no. 52 (2001).

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

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