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2. Exploring Energy Poverty: Toward a Comprehensive Predictive Framework. (2025). McLellan, Benjamin Craig ; Chapman, Andrew ; Mochida, Takako.
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2. Toward Proactive Policy Design: Identifying To-Be Energy-Poor Households Using Shap for Early Intervention. (2025). Freitas, Diogo Nuno ; Ferm, Eduardo ; Budra, Santiago.
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3. A Comparative Analysis of Machine Learning Algorithms in Energy Poverty Prediction. (2025). Damigos, Dimitris ; Kaliampakos, Dimitris ; Mirasgedis, Sevastianos ; Tourkolias, Christos ; Papada, Lefkothea ; Kalfountzou, Elpida.
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11. Artificial Neural Networks as a Tool to Understand Complex Energy Poverty Relationships: The Case of Greece. (2024). Papada, Lefkothea ; Kaliampakos, Dimitris.
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13. Forecasting energy poverty using different machine learning techniques for Missouri. (2024). Sykuta, Michael ; Ohler, Adrienne ; Balkissoon, Sarah ; Fox, Neil ; Lupo, Anthony ; Beetstra, Margaret ; Miller, Steve J ; Penny, Stephen G ; Haupt, Sue Ellen.
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14. Energy poverty prediction in the United Kingdom: A machine learning approach. (2024). Abdul, Zrar Khald ; del Rio, Dylan Furszyfer ; al Kez, Dlzar ; Foley, Aoife.
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15. Targeting SDG7: Identifying heterogeneous energy dilemmas for socially disadvantaged groups in India using machine learning. (2024). Yang, Shiyu ; Li, Jun.
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16. Turning the page on energy poverty? Quasi-experimental evidence on education and energy poverty in Zimbabwe. (2024). Makate, Marshall.
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17. Combining energy subsidies is not free: distributional effects and energy poverty. (2024). Mara, Ibez Martn ; Milena, Poggiese.
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18. Multidimensional Energy Poverty in China: Measurement and Spatio-Temporal Disparities Characteristics. (2023). Geng, Hong ; Wang, FU ; Zha, Donglan ; Zhang, Chaoqun.
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19. Measuring and Analyzing the Welfare Effects of Energy Poverty in Rural China Based on a Multi-Dimensional Energy Poverty Index. (2023). Xie, Yuxiang.
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20. Energy Poverty and Low Carbon Energy Transition. (2023). Kyriakopoulos, Grigorios L ; Streimikiene, Dalia.
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21. Energy poverty prediction and effective targeting for just transitions with machine learning. (2023). Lynch, Muireann ; Reaos, Miguel Tovar ; Spandagos, Constantine.
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22. A novel energy poverty evaluation: Study of the European Union countries. (2023). Pishahang, Mohammad ; Hasheminasab, Hamidreza ; Streimikiene, Dalia.
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23. Energy poverty prediction and effective targeting for just transitions with machine learning. (2023). Spandagos, Constantine ; Lynch, Muireann A ; Tovar, Miguel Angel.
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24. Linking Housing Conditions and Energy Poverty: From a Perspective of Household Energy Self-Restriction. (2022). Chen, Keyu ; Feng, Chao.
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25. Energy Poverty as a Current Problem in the Light of Economic and Social Challenges. (2022). Piwowar, Arkadiusz.
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27. Examining the multidimensional energy poverty trap and its determinants: An empirical analysis at household and community levels in six provinces of China. (2022). Huang, Yatao ; Guo, Xuanxuan ; Jiao, Wenxian ; Wang, Kang ; Chen, Jingyang ; Li, Erling ; Yan, Yutong.
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28. Childhood adversity and energy poverty. (2022). tani, max ; Smyth, Russell ; Guo, Liwen ; Cheng, Zhiming.
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29. Empirical Evidence on the Incidence and Persistence of Energy Poverty in Australia. (2022). Brown, Heather ; Veratoscano, Esperanza.
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