Statistical Learning for Nonlinear Dynamical Systems with Applications to Aircraft-UAV Collisions

Cites Work

Title not available (Why is that?)
An Explicit Link between Gaussian Fields and Gaussian Markov Random Fields: The Stochastic Partial Differential Equation Approach
Machine learning of linear differential equations using Gaussian processes
Hidden physics models: machine learning of nonlinear partial differential equations
Projection-based model reduction: formulations for physics-based machine learning
Reduced order modeling for nonlinear structural analysis using Gaussian process regression
Physics-informed neural networks: a deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations
Parallel partial Gaussian process emulation for computer models with massive output
A survey of projection-based model reduction methods for parametric dynamical systems
The Finite Element Method: Theory, Implementation, and Applications
Introduction to the explicit finite element method for nonlinear transient dynamics.
An Efficient Surrogate Model for Emulation and Physics Extraction of Large Eddy Simulations
Numerical Gaussian Processes for Time-Dependent and Nonlinear Partial Differential Equations
Deep Hidden Physics Models: Deep Learning of Nonlinear Partial Differential Equations
Coupling Computer Models through Linking Their Statistical Emulators
Learning and meta-learning of stochastic advection–diffusion–reaction systems from sparse measurements
Advanced Spatial Modeling with Stochastic Partial Differential Equations Using R and INLA
fPINNs: Fractional Physics-Informed Neural Networks
Maximum projection designs for computer experiments
Stochastic Partial Differential Equation Based Modelling of Large Space–Time Data Sets
Gaussian Process Subspace Prediction for Model Reduction
Statistical Modeling for Spatio-Temporal Data From Stochastic Convection-Diffusion Processes
A Multifidelity Function-on-Function Model Applied to an Abdominal Aortic Aneurysm
Gaussian Process Assisted Active Learning of Physical Laws
Function-on-Function Kriging, With Applications to Three-Dimensional Printing of Aortic Tissues

This page was built for publication: Statistical Learning for Nonlinear Dynamical Systems with Applications to Aircraft-UAV Collisions

Report a bug (only for logged in users!)Click here to report a bug for this page (MaRDI item Q6631167)