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Physics-informed machine learning

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

Papers

Showing 101150 of 192 papers

TitleStatusHype
Physics-informed neural networks for pathloss prediction0
A Metalearning Approach for Physics-Informed Neural Networks (PINNs): Application to Parameterized PDEs0
Residual-based physics-informed transfer learning: A hybrid method for accelerating long-term CFD simulations via deep learning0
Scalable Neural Dynamic Equivalence for Power Systems0
Predicting 3D Rigid Body Dynamics with Deep Residual Network0
Prediction of Reynolds Stresses in High-Mach-Number Turbulent Boundary Layers using Physics-Informed Machine Learning0
QRnet: optimal regulator design with LQR-augmented neural networks0
Randomized Physics-Informed Machine Learning for Uncertainty Quantification in High-Dimensional Inverse Problems0
Replication Study: Enhancing Hydrological Modeling with Physics-Guided Machine Learning0
Safe Physics-Informed Machine Learning for Dynamics and Control0
Scalable algorithms for physics-informed neural and graph networks0
Scientific machine learning in Hydrology: a unified perspective0
Self-tuning moving horizon estimation of nonlinear systems via physics-informed machine learning Koopman modeling0
Slow Invariant Manifolds of Singularly Perturbed Systems via Physics-Informed Machine Learning0
Solving engineering eigenvalue problems with neural networks using the Rayleigh quotient0
Spectrally Informed Learning of Fluid Flows0
Structural Constraints for Physics-augmented Learning0
Tensor Basis Gaussian Process Models of Hyperelastic Materials0
Toward Knowledge-Guided AI for Inverse Design in Manufacturing: A Perspective on Domain, Physics, and Human-AI Synergy0
Toward Physics-Informed Machine Learning for Data Center Operations: A Tropical Case Study0
Towards Physically Interpretable World Models: Meaningful Weakly Supervised Representations for Visual Trajectory Prediction0
Transcriptome and Redox Proteome Reveal Temporal Scales of Carbon Metabolism Regulation in Model Cyanobacteria Under Light Disturbance0
Transforming Future Data Center Operations and Management via Physical AI0
Understanding Generalization in Physics Informed Models through Affine Variety Dimensions0
Universal Battery Performance and Degradation Model for Electric Aircraft0
Update hydrological states or meteorological forcings? Comparing data assimilation methods for differentiable hydrologic models0
Valuation of Public Bus Electrification with Open Data0
When Physics Meets Machine Learning: A Survey of Physics-Informed Machine Learning0
Physics-Informed Machine Learning for Efficient Reconfigurable Intelligent Surface Design0
Potential failures of physics-informed machine learning in traffic flow modeling: theoretical and experimental analysis0
TS-PIELM: Time-Stepping Physics-Informed Extreme Learning Machine Facilitates Soil Consolidation Analyses0
AutoMat: Accelerated Computational Electrochemical systems Discovery0
A Comparative Evaluation of Additive Separability Tests for Physics-Informed Machine Learning0
A comprehensive and FAIR comparison between MLP and KAN representations for differential equations and operator networks0
A Critical Review of Physics-Informed Machine Learning Applications in Subsurface Energy Systems0
A Data-driven Crowd Simulation Framework Integrating Physics-informed Machine Learning with Navigation Potential Fields0
AdjointNet: Constraining machine learning models with physics-based codes0
Advancing Hybrid Quantum Neural Network for Alternative Current Optimal Power Flow0
AI Foundation Models for Weather and Climate: Applications, Design, and Implementation0
A Mechanism-Learning Deeply Coupled Model for Remote Sensing Retrieval of Global Land Surface Temperature0
A Multimodal Physics-Informed Neural Network Approach for Mean Radiant Temperature Modeling0
An interpretation of the Brownian bridge as a physics-informed prior for the Poisson equation0
An operator preconditioning perspective on training in physics-informed machine learning0
Physics-informed machine learning for composition-process-property alloy design: shape memory alloy demonstration0
A Physics-Informed Machine Learning Approach for Solving Heat Transfer Equation in Advanced Manufacturing and Engineering Applications0
A Physics-Informed Machine Learning Approach for Solving Distributed Order Fractional Differential Equations0
A Physics-informed Machine Learning-based Control Method for Nonlinear Dynamic Systems with Highly Noisy Measurements0
A Physics-Informed Machine Learning for Electricity Markets: A NYISO Case Study0
A Physics-Informed Machine Learning Framework for Safe and Optimal Control of Autonomous Systems0
A Physics-Informed Machine Learning Model for Porosity Analysis in Laser Powder Bed Fusion Additive Manufacturing0
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