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Physics-informed machine learning

Machine learning used to represent physics-based and/or engineering models

Papers

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Showing 41–50 of 192 papers

TitleStatusHype
Safe Physics-Informed Machine Learning for Dynamics and Control—0
A Mechanism-Learning Deeply Coupled Model for Remote Sensing Retrieval of Global Land Surface Temperature—0
Physics-informed Modularized Neural Network for Advanced Building Control by Deep Reinforcement Learning—0
Transforming Future Data Center Operations and Management via Physical AI—0
Physics-informed machine learning for building performance simulation-A review of a nascent field—0
Physics-Informed Deep B-Spline Networks for Dynamical Systems—0
Further Exploration of Precise Binding Energies from Physics Informed Machine Learning and the Development of a Practical Ensemble Model—0
A Multimodal Physics-Informed Neural Network Approach for Mean Radiant Temperature Modeling—0
A physics-informed Bayesian optimization method for rapid development of electrical machines—0
An interpretation of the Brownian bridge as a physics-informed prior for the Poisson equation—0
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