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(2026). <i>Predicting Heterogeneous Treatment Effects Of Building Energy Saving Retrofits Using Causal Machine Learning</i>.","ieee":"K. Zalipski, D. R. Zapata Gonzalez, and O. Müller, “Predicting Heterogeneous Treatment Effects Of Building Energy Saving Retrofits Using Causal Machine Learning,” 2026.","ama":"Zalipski K, Zapata Gonzalez DR, Müller O. Predicting Heterogeneous Treatment Effects Of Building Energy Saving Retrofits Using Causal Machine Learning. 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Temporal causal feature selection for robust machine learning modelling of data center operations. <i>Applied Energy</i>, <i>417</i>, Article 127984. <a href=\"https://doi.org/10.1016/j.apenergy.2026.127984\">https://doi.org/10.1016/j.apenergy.2026.127984</a>","ieee":"D. R. Zapata Gonzalez, M. Meyer, K. Zalipski, and O. Müller, “Temporal causal feature selection for robust machine learning modelling of data center operations,” <i>Applied Energy</i>, vol. 417, Art. no. 127984, 2026, doi: <a href=\"https://doi.org/10.1016/j.apenergy.2026.127984\">10.1016/j.apenergy.2026.127984</a>.","chicago":"Zapata Gonzalez, David Ricardo, Marcel Meyer, Kevin Zalipski, and Oliver Müller. “Temporal Causal Feature Selection for Robust Machine Learning Modelling of Data Center Operations.” <i>Applied Energy</i> 417 (2026). <a href=\"https://doi.org/10.1016/j.apenergy.2026.127984\">https://doi.org/10.1016/j.apenergy.2026.127984</a>.","short":"D.R. Zapata Gonzalez, M. Meyer, K. Zalipski, O. 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