Machine learning based digital twin for stochastic nonlinear
multi-degree of freedom dynamical system

Machine learning based digital twin for stochastic nonlinear multi-degree of freedom dynamical system

29 March 2021

Papers citing "Machine learning based digital twin for stochastic nonlinear multi-degree of freedom dynamical system"

9 / 9 papers shown

Title
State estimation with limited sensors -- A deep learning based approach Y. Kumar Pranav Bahl S. Chakraborty 38 29 0 27 Jan 2021
Transfer learning based multi-fidelity physics informed deep neural network S. Chakraborty PINN OOD AI4CE 72 165 0 19 May 2020
Machine learning based digital twin for dynamical systems with multiple time-scales S. Chakraborty S. Adhikari AI4CE 38 87 0 12 May 2020
Simulation free reliability analysis: A physics-informed deep learning based approach S. Chakraborty AI4CE 33 16 0 04 May 2020
The role of surrogate models in the development of digital twins of dynamic systems S. Chakraborty S. Adhikari R. Ganguli SyDa 48 106 0 25 Jan 2020
Aleatoric and Epistemic Uncertainty in Machine Learning: An Introduction to Concepts and Methods Eyke Hüllermeier Willem Waegeman PER UD 244 1,415 0 21 Oct 2019
An Energy Approach to the Solution of Partial Differential Equations in Computational Mechanics via Machine Learning: Concepts, Implementation and Applications E. Samaniego C. Anitescu S. Goswami Vien Minh Nguyen-Thanh Hongwei Guo Khader M. Hamdia Timon Rabczuk X. Zhuang PINN AI4CE 205 1,379 0 27 Aug 2019
$Transfer learning enhanced physics informed neural network for phase-field modeling of fracture$ Transfer learning enhanced physics informed neural network for phase-field modeling of fracture S. Goswami C. Anitescu S. Chakraborty Timon Rabczuk PINN 70 610 0 04 Jul 2019
A Gaussian process latent force model for joint input-state estimation in linear structural systems R. Nayek S. Chakraborty S. Narasimhan 25 91 0 29 Mar 2019

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