2 citations · 4 across the 5 of their papers we have counts for
5 papers
Surrogate modeling for convection-dominated parametric problems based on error learning
Lihong Feng, Ali Hassan, Shuwen Sun
Convection-dominated problems are known for their slow Kolmogorov -width decays and are challenging for model order reduction (MOR). In this work, we propose a hybrid surrogate…
Spatially-Enhanced Temporal Fusion Transformer: Interpretable Multi-Output Prediction for Parametric Dynamical Systems with Time-Varying Inputs
Shuwen Sun, Lihong Feng, Peter Benner
We explore the promising performance of a transformer model in predicting outputs of parametric dynamical systems with external time-varying input signals. The outputs of such syst…
Data-Augmented Predictive Deep Neural Network: Enhancing the extrapolation capabilities of non-intrusive surrogate models
Shuwen Sun, Lihong Feng, Peter Benner
Numerically solving a large parametric nonlinear dynamical system is challenging due to its high complexity and the high computational costs. In recent years, machine-learning-aide…
Parametric Dynamic Mode Decomposition for nonlinear parametric dynamical systems
Shuwen Sun, Lihong Feng, Hoon Seng Chan +4
A non-intrusive model order reduction (MOR) method that combines features of the dynamic mode decomposition (DMD) and the radial basis function (RBF) network is proposed to predict…
Synthetic Tumors Make AI Segment Tumors Better
Qixin Hu, Junfei Xiao, Yixiong Chen +4
We develop a novel strategy to generate synthetic tumors. Unlike existing works, the tumors generated by our strategy have two intriguing advantages: (1) realistic in shape and tex…