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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 26–50 of 192 papers

TitleStatusHype
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
Update hydrological states or meteorological forcings? Comparing data assimilation methods for differentiable hydrologic models—0
A Physics-Informed Machine Learning Framework for Safe and Optimal Control of Autonomous Systems—0
Generalizable and Fast Surrogates: Model Predictive Control of Articulated Soft Robots using Physics-Informed Neural Networks—0
Understanding Generalization in Physics Informed Models through Affine Variety Dimensions—0
PDE-DKL: PDE-constrained deep kernel learning in high dimensionalityCode0
Empirical modeling and hybrid machine learning framework for nucleate pool boiling on microchannel structured surfaces—0
Physics-Informed Machine Learning for Efficient Reconfigurable Intelligent Surface Design—0
Physics-Informed Machine Learning for Microscale Drying of Plant-Based Foods: A Systematic Review of Computational Models and Experimental Insights—0
KKANs: Kurkova-Kolmogorov-Arnold Networks and Their Learning Dynamics—0
Towards Physically Interpretable World Models: Meaningful Weakly Supervised Representations for Visual Trajectory Prediction—0
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
Non-overlapping, Schwarz-type Domain Decomposition Method for Physics and Equality Constrained Artificial Neural NetworksCode0
Physics-informed kernel learningCode0
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