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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 126–150 of 192 papers

TitleStatusHype
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
Physics-Informed Machine Learning for Efficient Reconfigurable Intelligent Surface Design—0
Potential failures of physics-informed machine learning in traffic flow modeling: theoretical and experimental analysis—0
TS-PIELM: Time-Stepping Physics-Informed Extreme Learning Machine Facilitates Soil Consolidation Analyses—0
AutoMat: Accelerated Computational Electrochemical systems Discovery—0
A Comparative Evaluation of Additive Separability Tests for Physics-Informed Machine Learning—0
A comprehensive and FAIR comparison between MLP and KAN representations for differential equations and operator networks—0
A Critical Review of Physics-Informed Machine Learning Applications in Subsurface Energy Systems—0
A Data-driven Crowd Simulation Framework Integrating Physics-informed Machine Learning with Navigation Potential Fields—0
AdjointNet: Constraining machine learning models with physics-based codes—0
Advancing Hybrid Quantum Neural Network for Alternative Current Optimal Power Flow—0
AI Foundation Models for Weather and Climate: Applications, Design, and Implementation—0
A Mechanism-Learning Deeply Coupled Model for Remote Sensing Retrieval of Global Land Surface Temperature—0
A Multimodal Physics-Informed Neural Network Approach for Mean Radiant Temperature Modeling—0
An interpretation of the Brownian bridge as a physics-informed prior for the Poisson equation—0
An operator preconditioning perspective on training in physics-informed machine learning—0
Physics-informed machine learning for composition-process-property alloy design: shape memory alloy demonstration—0
A Physics-Informed Machine Learning Approach for Solving Heat Transfer Equation in Advanced Manufacturing and Engineering Applications—0
A Physics-Informed Machine Learning Approach for Solving Distributed Order Fractional Differential Equations—0
A Physics-informed Machine Learning-based Control Method for Nonlinear Dynamic Systems with Highly Noisy Measurements—0
A Physics-Informed Machine Learning for Electricity Markets: A NYISO Case Study—0
A Physics-Informed Machine Learning Framework for Safe and Optimal Control of Autonomous Systems—0
A Physics-Informed Machine Learning Model for Porosity Analysis in Laser Powder Bed Fusion Additive Manufacturing—0
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