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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 51–100 of 192 papers

TitleStatusHype
Physics-informed Discretization-independent Deep Compositional Operator NetworkCode0
DSSRNN: Decomposition-Enhanced State-Space Recurrent Neural Network for Time-Series AnalysisCode0
PDE-DKL: PDE-constrained deep kernel learning in high dimensionalityCode0
Unsupervised Discovery of Extreme Weather Events Using Universal Representations of Emergent OrganizationCode0
Hyperspectral Blind Unmixing using a Double Deep Image PriorCode0
Π-ML: A dimensional analysis-based machine learning parameterization of optical turbulence in the atmospheric surface layerCode0
Physics Encoded Blocks in Residual Neural Network Architectures for Digital Twin ModelsCode0
Physics-Informed Calibration of Aeromagnetic Compensation in Magnetic Navigation Systems using Liquid Time-Constant NetworksCode0
An analysis of Universal Differential Equations for data-driven discovery of Ordinary Differential EquationsCode0
Reconstructing Physics-Informed Machine Learning for Traffic Flow Modeling: a Multi-Gradient Descent and Pareto Learning ApproachCode0
Towards Size-Independent Generalization Bounds for Deep Operator NetsCode0
RL for Mitigating Cascading Failures: Targeted Exploration via Sensitivity FactorsCode0
Physics-Informed Deep Neural Networks for Transient Electromagnetic AnalysisCode0
Estimating irregular water demands with physics-informed machine learning to inform leakage detectionCode0
Physical Data Embedding for Memory Efficient AI—0
Numerical Approximation in CFD Problems Using Physics Informed Machine Learning—0
Numerical Gaussian process Kalman filtering for spatiotemporal systems—0
Optimal Power Flow in Highly Renewable Power System Based on Attention Neural Networks—0
Overview of Physics-Informed Machine Learning Inversion of Geophysical Data—0
Grid-SiPhyR: An end-to-end learning to optimize framework for combinatorial problems in power systems—0
Physics-Informed Computer Vision: A Review and Perspectives—0
Physics-informed ConvNet: Learning Physical Field from a Shallow Neural Network—0
Physics-Informed Deep B-Spline Networks for Dynamical Systems—0
Physics-informed Gaussian process model for Euler-Bernoulli beam elements—0
Physics-Informed Induction Machine Modelling—0
Physics-informed machine learning for Structural Health Monitoring—0
Physics Informed Machine Learning for Chemistry Tabulation—0
Physics-Informed Machine Learning for Modeling and Control of Dynamical Systems—0
Physics-informed Machine Learning for Calibrating Macroscopic Traffic Flow Models—0
Physics-Informed Machine Learning for Microscale Drying of Plant-Based Foods: A Systematic Review of Computational Models and Experimental Insights—0
A physics-informed Bayesian optimization method for rapid development of electrical machines—0
Physics-informed machine learning for building performance simulation-A review of a nascent field—0
Physics-informed Machine Learning for Battery Pack Thermal Management—0
Physics-Informed Machine Learning for Data Anomaly Detection, Classification, Localization, and Mitigation: A Review, Challenges, and Path Forward—0
Physics-Informed Machine Learning for Grade Prediction in Froth Flotation—0
Physics-informed machine learning for moving load problems—0
Physics-Informed Machine Learning for Seismic Response Prediction OF Nonlinear Steel Moment Resisting Frame Structures—0
Physics-informed machine learning for sensor fault detection with flight test data—0
Physics-Informed Machine Learning for Smart Additive Manufacturing—0
Physics-Informed Machine Learning for the Inverse Design of Wave Scattering Clusters—0
Physics-Informed Machine Learning Models for Predicting the Progress of Reactive-Mixing—0
Physics-informed Machine Learning of Parameterized Fundamental Diagrams—0
Physics-Informed Machine Learning of Argon Gas-Driven Melt Pool Dynamics—0
Physics-informed machine learning of redox flow battery based on a two-dimensional unit cell model—0
Physics-informed machine learning of the correlation functions in bulk fluids—0
Physics-Informed Machine Learning On Polar Ice: A Survey—0
Physics Informed Machine Learning (PIML) methods for estimating the remaining useful lifetime (RUL) of aircraft engines—0
Physics-Informed Machine Learning Regulated by Finite Element Analysis for Simulation Acceleration of Laser Powder Bed Fusion—0
Physics-Informed Machine Learning Towards A Real-Time Spacecraft Thermal Simulator—0
Physics-informed Modularized Neural Network for Advanced Building Control by Deep Reinforcement Learning—0
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