activity
20192022
most citedOn the accuracy of stiff-accurate diagonal implicit Runge-Kutta methods for finite volume based Navier-Stokes equations

4 citations · 5 across the 4 of their papers we have counts for

collaborators

7 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.LG2020

Applications of shapelet transform to time series classification of earthquake, wind and wave data

Monica Arul, Ahsan Kareem

Autonomous detection of desired events from large databases using time series classification is becoming increasingly important in civil engineering as a result of continued long-t…

cs.LG20191 cited

Shapelets for earthquake detection

Monica Arul, Ahsan Kareem

This paper introduces EQShapelets (EarthQuake Shapelets) a time-series shape-based approach embedded in machine learning to autonomously detect earthquakes. It promises to overcome…

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…