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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 61–70 of 192 papers

TitleStatusHype
DSSRNN: Decomposition-Enhanced State-Space Recurrent Neural Network for Time-Series AnalysisCode0
RL for Mitigating Cascading Failures: Targeted Exploration via Sensitivity FactorsCode0
Physics Encoded Blocks in Residual Neural Network Architectures for Digital Twin ModelsCode0
Physics-informed Machine Learning for Battery Pack Thermal Management—0
Advancing Hybrid Quantum Neural Network for Alternative Current Optimal Power Flow—0
A Data-driven Crowd Simulation Framework Integrating Physics-informed Machine Learning with Navigation Potential Fields—0
From PINNs to PIKANs: Recent Advances in Physics-Informed Machine Learning—0
Transcriptome and Redox Proteome Reveal Temporal Scales of Carbon Metabolism Regulation in Model Cyanobacteria Under Light Disturbance—0
Structural Constraints for Physics-augmented Learning—0
DeepONet for Solving Nonlinear Partial Differential Equations with Physics-Informed Training—0
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