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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 101–125 of 192 papers

TitleStatusHype
Predicting 3D Rigid Body Dynamics with Deep Residual Network—0
Prediction of Reynolds Stresses in High-Mach-Number Turbulent Boundary Layers using Physics-Informed Machine Learning—0
QRnet: optimal regulator design with LQR-augmented neural networks—0
Randomized Physics-Informed Machine Learning for Uncertainty Quantification in High-Dimensional Inverse Problems—0
Replication Study: Enhancing Hydrological Modeling with Physics-Guided Machine Learning—0
Safe Physics-Informed Machine Learning for Dynamics and Control—0
Scalable algorithms for physics-informed neural and graph networks—0
Scientific machine learning in Hydrology: a unified perspective—0
Self-tuning moving horizon estimation of nonlinear systems via physics-informed machine learning Koopman modeling—0
Slow Invariant Manifolds of Singularly Perturbed Systems via Physics-Informed Machine Learning—0
Solving engineering eigenvalue problems with neural networks using the Rayleigh quotient—0
Spectrally Informed Learning of Fluid Flows—0
Structural Constraints for Physics-augmented Learning—0
Tensor Basis Gaussian Process Models of Hyperelastic Materials—0
Toward Knowledge-Guided AI for Inverse Design in Manufacturing: A Perspective on Domain, Physics, and Human-AI Synergy—0
Toward Physics-Informed Machine Learning for Data Center Operations: A Tropical Case Study—0
Towards Physically Interpretable World Models: Meaningful Weakly Supervised Representations for Visual Trajectory Prediction—0
Transcriptome and Redox Proteome Reveal Temporal Scales of Carbon Metabolism Regulation in Model Cyanobacteria Under Light Disturbance—0
Transforming Future Data Center Operations and Management via Physical AI—0
Understanding Generalization in Physics Informed Models through Affine Variety Dimensions—0
Universal Battery Performance and Degradation Model for Electric Aircraft—0
Update hydrological states or meteorological forcings? Comparing data assimilation methods for differentiable hydrologic models—0
Valuation of Public Bus Electrification with Open Data—0
When Physics Meets Machine Learning: A Survey of Physics-Informed Machine Learning—0
Multi-scale Digital Twin: Developing a fast and physics-informed surrogate model for groundwater contamination with uncertain climate models—0
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