Papers matching “physics-guided machine learning” 20
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Physics-based machine learning for modeling thermo-hydraulic processes in a coaxial deep borehole heat exchanger, considering an explicit reservoir-wellbore representation: A case study of Cornwall, UK
Dimitra Teza, Ryan Santoso, Nora Koltzer, Denise Degen, Tony Bennett, Florian Wellmann
0citations -
Perspectives of physics-based machine learning strategies for geoscientific applications governed by partial differential equations2023 Geoscientific model development article Physics and Astronomy Model Reduction and Neural Networks Open access
Denise Degen, Daniel Caviedes‐Voullième, Susanne Buiter, Harrie‐Jan Hendricks Franssen, Harry Vereecken, Ana González‐Nicolás, +1 more
39citations -
Physics-Based Machine Learning: Opportunities and Challenges for Mantle Convection2026 Zenodo (CERN European Organization for Nuclear Research) dataset Physics and Astronomy Model Reduction and Neural Networks Open access
Marilina Valatsou, Denise Degen, Juliane Dannberg, René Gassmöller, Florian Wellmann
0citations -
Physics-Based Machine Learning: Opportunities and Challenges for Mantle Convection2026 Zenodo (CERN European Organization for Nuclear Research) dataset Physics and Astronomy Model Reduction and Neural Networks Open access
Marilina Valatsou, Denise Degen, Juliane Dannberg, René Gassmöller, Florian Wellmann
0citations -
Improving the Timing Resolution of Positron Emission Tomography Detectors Using Boosted Learning—A Residual Physics Approach2023 IEEE Transactions on Neural Networks and Learning Systems article Physics and Astronomy Radiation Detection and Scintillator Technologies Open access
Stephan Naunheim, Yannick Kuhl, David Schug, Volkmar Schulz, Florian Mueller
24citations
20 results