David Ricardo Zapata Gonzalez

david.zapata@uni-paderborn.de
ID
105506

3 Publications

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[3]
2025 | Conference Paper | LibreCat-ID: 60680
Zapata Gonzalez, D. R., Meyer, M., & Müller, O. (2025). Bridging the gap between data-driven and theory-driven modelling – leveraging causal machine learning for integrative modelling of dynamical systems. European Conference on Information Systems, Amman, Jordan.
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[2]
2025 | Conference Paper | LibreCat-ID: 63397 | OA
Zapata Gonzalez, D. R., Brennig, K., Benkert, K., Schlosser, F., & Müller, O. (2025). Process Mining for Robust Heat Integration through Process- and Product-Centric Energy Demand Modeling. ACM SIGEnergy Energy Informatics Review, 5(3), 19–31. https://doi.org/10.1145/3777518.3777520
LibreCat | DOI | Download (ext.)
 
[1]
2025 | Conference Paper | LibreCat-ID: 63400 | OA
Zapata Gonzalez, D. R., Meyer, M., & Müller, O. (2025). Causal Machine Learning Approaches for Modelling Data Center Heat Recovery: A Physical Testbed Study. ACM SIGEnergy Energy Informatics Review, 5(2), 4–10. https://doi.org/10.1145/3757892.3757893
LibreCat | DOI | Download (ext.)
 
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3 Publications

Mark all

[3]
2025 | Conference Paper | LibreCat-ID: 60680
Zapata Gonzalez, D. R., Meyer, M., & Müller, O. (2025). Bridging the gap between data-driven and theory-driven modelling – leveraging causal machine learning for integrative modelling of dynamical systems. European Conference on Information Systems, Amman, Jordan.
LibreCat | Download (ext.)
 
[2]
2025 | Conference Paper | LibreCat-ID: 63397 | OA
Zapata Gonzalez, D. R., Brennig, K., Benkert, K., Schlosser, F., & Müller, O. (2025). Process Mining for Robust Heat Integration through Process- and Product-Centric Energy Demand Modeling. ACM SIGEnergy Energy Informatics Review, 5(3), 19–31. https://doi.org/10.1145/3777518.3777520
LibreCat | DOI | Download (ext.)
 
[1]
2025 | Conference Paper | LibreCat-ID: 63400 | OA
Zapata Gonzalez, D. R., Meyer, M., & Müller, O. (2025). Causal Machine Learning Approaches for Modelling Data Center Heat Recovery: A Physical Testbed Study. ACM SIGEnergy Energy Informatics Review, 5(2), 4–10. https://doi.org/10.1145/3757892.3757893
LibreCat | DOI | Download (ext.)
 
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