51 citations · 117 across the 12 of their papers we have counts for
5 papers · 1 filter
Learning to simulate partially known spatio-temporal dynamics with trainable difference operators
Xiang Huang, Zhuoyuan Li, Hongsheng Liu +4
Recently, using neural networks to simulate spatio-temporal dynamics has received a lot of attention. However, most existing methods adopt pure data-driven black-box models, which…
Analysis of the Decoder Width for Parametric Partial Differential Equations
Zhanhong Ye, Hongsheng Liu, Zidong Wang +1
Recently, Meta-Auto-Decoder (MAD) was proposed as a novel reduced order model (ROM) for solving parametric partial differential equations (PDEs), and the best possible performance…
Prediction of transonic flow over supercritical airfoils using geometric-encoding and deep-learning strategies
Zhiwen Deng, Jing Wang, Hongsheng Liu +7
The Reynolds-averaged Navier-Stokes equation for compressible flow over supercritical airfoils under various flow conditions must be rapidly and accurately solved to shorten design…
Adaptive Rotated Convolution for Rotated Object Detection
Yifan Pu, Yiru Wang, Zhuofan Xia +6
Rotated object detection aims to identify and locate objects in images with arbitrary orientation. In this scenario, the oriented directions of objects vary considerably across dif…
Solving Boltzmann equation with neural sparse representation
Zhengyi Li, Yanli Wang, Hongsheng Liu +2
We consider the neural sparse representation to solve Boltzmann equation with BGK and quadratic collision model, where a network-based ansatz that can approximate the distribution…