7 citations · 19 across the 6 of their papers we have counts for
5 papers · 1 filter
Unscented Kalman Inversion: Efficient Gaussian Approximation to the Posterior Distribution
Daniel Z. Huang, Jiaoyang Huang
The unscented Kalman inversion (UKI) method presented in [1] is a general derivative-free approach for the inverse problem. UKI is particularly suitable for inverse problems where…
Improve Unscented Kalman Inversion With Low-Rank Approximation and Reduced-Order Model
Daniel Z. Huang, Jiaoyang Huang
The unscented Kalman inversion (UKI) presented in [1] is a general derivative-free approach to solving the inverse problem. UKI is particularly suitable for inverse problems where…
Learning Constitutive Relations using Symmetric Positive Definite Neural Networks
Kailai Xu, Daniel Z. Huang, Eric Darve
We present the Cholesky-factored symmetric positive definite neural network (SPD-NN) for modeling constitutive relations in dynamical equations. Instead of directly predicting the…
High-order partitioned spectral deferred correction solvers for multiphysics problems
Daniel Z. Huang, Will Pazner, Per-Olof Persson +1
We present an arbitrarily high-order, conditionally stable, partitioned spectral deferred correction (SDC) method for solving multiphysics problems using a sequence of pre-existing…
Learning Constitutive Relations from Indirect Observations Using Deep Neural Networks
Daniel Z. Huang, Kailai Xu, Charbel Farhat +1
We present a new approach for predictive modeling and its uncertainty quantification for mechanical systems, where coarse-grained models such as constitutive relations are derived…