33 citations · 53 across the 2 of their papers we have counts for
2 papers
physics.flu-dyn2021★ 33 cited
Physics-driven Learning of the Steady Navier-Stokes Equations using Deep Convolutional Neural Networks
Hao Ma, Yuxuan Zhang, Nils Thuerey +2
Recently, physics-driven deep learning methods have shown particular promise for the prediction of physical fields, especially to reduce the dependency on large amounts of pre-comp…
physics.comp-ph2020★ 20 cited
A Combined Data-driven and Physics-driven Method for Steady Heat Conduction Prediction using Deep Convolutional Neural Networks
Hao Ma, Xiangyu Hu, Yuxuan Zhang +2
With several advantages and as an alternative to predict physics field, machine learning methods can be classified into two distinct types: data-driven relying on training data and…