activity
20192022
most citedFeature Importance in a Deep Learning Climate Emulator

2 citations · 2 across the 3 of their papers we have counts for

collaborators

5 papers

physics.comp-ph2022

A Deep Finite Difference Emulator for the Fast Simulation of Coupled Viscous Burgers' Equation

Xihaier Luo, Yihui Ren, Wei Xu +3

This work proposes a deep learning-based emulator for the efficient computation of the coupled viscous Burgers' equation with random initial conditions. In a departure from traditi…

cs.LG2022

A Machine Learning-based Characterization Framework for Parametric Representation of Nonlinear Sloshing

Xihaier Luo, Ahsan Kareem, Liting Yu +1

The growing interest in creating a parametric representation of liquid sloshing inside a container stems from its practical applications in modern engineering systems. The resonant…

cs.LG20212 cited

Feature Importance in a Deep Learning Climate Emulator

Wei Xu, Xihaier Luo, Yihui Ren +3

We present a study using a class of post-hoc local explanation methods i.e., feature importance methods for "understanding" a deep learning (DL) emulator of climate. Specifically,…

eess.IV2019

Deep convolutional neural networks for uncertainty propagation in random fields

Xihaier Luo, Ahsan Kareem

The development of a reliable and robust surrogate model is often constrained by the dimensionality of the problem. For a system with high-dimensional inputs/outputs (I/O), convent…

stat.ML2019

Bayesian deep learning with hierarchical prior: Predictions from limited and noisy data

Xihaier Luo, Ahsan Kareem

Datasets in engineering applications are often limited and contaminated, mainly due to unavoidable measurement noise and signal distortion. Thus, using conventional data-driven app…