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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
A Physics-Informed Machine Learning Approach for Solving Distributed Order Fractional Differential Equations—0
State-space models are accurate and efficient neural operators for dynamical systemsCode0
(Un)supervised Learning of Maximal Lyapunov Functions—0
Spectrally Informed Learning of Fluid Flows—0
Machine Learning with Physics Knowledge for Prediction: A Survey—0
Enhanced BPINN Training Convergence in Solving General and Multi-scale Elliptic PDEs with Noise—0
Physics-Informed Machine Learning for Grade Prediction in Froth Flotation—0
Self-tuning moving horizon estimation of nonlinear systems via physics-informed machine learning Koopman modeling—0
Adaptive Training of Grid-Dependent Physics-Informed Kolmogorov-Arnold NetworksCode2
Inferring turbulent velocity and temperature fields and their statistics from Lagrangian velocity measurements using physics-informed Kolmogorov-Arnold Networks—0
Separable DeepONet: Breaking the Curse of Dimensionality in Physics-Informed Machine LearningCode0
Physical Data Embedding for Memory Efficient AI—0
Differentiable Neural-Integrated Meshfree Method for Forward and Inverse Modeling of Finite Strain HyperelasticityCode0
Deep Learning Evidence for Global Optimality of Gerver's SofaCode0
Physics-Informed Machine Learning for Smart Additive Manufacturing—0
Predicting 3D Rigid Body Dynamics with Deep Residual Network—0
Physics-Informed Machine Learning Towards A Real-Time Spacecraft Thermal Simulator—0
Finite Operator Learning: Bridging Neural Operators and Numerical Methods for Efficient Parametric Solution and Optimization of PDEsCode1
Identifying Ordinary Differential Equations for Data-efficient Model-based Reinforcement Learning—0
Physics Informed Machine Learning (PIML) methods for estimating the remaining useful lifetime (RUL) of aircraft engines—0
Differentiable Predictive Control for Large-Scale Urban Road NetworksCode0
Adapting Physics-Informed Neural Networks to Improve ODE Optimization in Mosquito Population DynamicsCode0
A comprehensive and FAIR comparison between MLP and KAN representations for differential equations and operator networks—0
Non-destructive Degradation Pattern Decoupling for Ultra-early Battery Prototype Verification Using Physics-informed Machine LearningCode2
Physics-Informed Machine Learning On Polar Ice: A Survey—0
Physics-informed Discretization-independent Deep Compositional Operator NetworkCode0
Data-driven AC Optimal Power Flow with Physics-informed Learning and Calibrations—0
Label Propagation Training Schemes for Physics-Informed Neural Networks and Gaussian Processes—0
Fully-fused Multi-Layer Perceptrons on Intel Data Center GPUsCode2
Evaluation of GlassNet for physics-informed machine learning of glass stability and glass-forming abilityCode0
Physics-Informed Machine Learning for Seismic Response Prediction OF Nonlinear Steel Moment Resisting Frame Structures—0
Physics-Informed Machine Learning for the Inverse Design of Wave Scattering Clusters—0
Discovering Artificial Viscosity Models for Discontinuous Galerkin Approximation of Conservation Laws using Physics-Informed Machine Learning—0
Replication Study: Enhancing Hydrological Modeling with Physics-Guided Machine Learning—0
Kolmogorov n-Widths for Multitask Physics-Informed Machine Learning (PIML) Methods: Towards Robust MetricsCode0
Physics-informed machine learning as a kernel methodCode0
Social Physics Informed Diffusion Model for Crowd SimulationCode1
A Review of Physics-Informed Machine Learning Methods with Applications to Condition Monitoring and Anomaly Detection—0
Physics-Informed Calibration of Aeromagnetic Compensation in Magnetic Navigation Systems using Liquid Time-Constant NetworksCode0
A Physics-informed machine learning model for time-dependent wave runup prediction—0
A Gaussian Process Framework for Solving Forward and Inverse Problems Involving Nonlinear Partial Differential EquationsCode1
A Comparative Evaluation of Additive Separability Tests for Physics-Informed Machine Learning—0
Randomized Physics-Informed Machine Learning for Uncertainty Quantification in High-Dimensional Inverse Problems—0
Value Approximation for Two-Player General-Sum Differential Games with State ConstraintsCode0
Optimal Power Flow in Highly Renewable Power System Based on Attention Neural Networks—0
Neural-Integrated Meshfree (NIM) Method: A differentiable programming-based hybrid solver for computational mechanics—0
A Physics-informed Machine Learning-based Control Method for Nonlinear Dynamic Systems with Highly Noisy Measurements—0
Filtered Partial Differential Equations: a robust surrogate constraint in physics-informed deep learning framework—0
Zero Coordinate Shift: Whetted Automatic Differentiation for Physics-informed Operator LearningCode0
Overview of Physics-Informed Machine Learning Inversion of Geophysical Data—0
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