activity
20182024
most citedEnd-to-end Wind Turbine Wake Modelling with Deep Graph Representation Learning

73 citations · 144 across the 11 of their papers we have counts for

collaborators
Showing 2022Show all

5 papers · 1 filter

cs.LG2022★ 73 cited

End-to-end Wind Turbine Wake Modelling with Deep Graph Representation Learning

Siyi Li, Mingrui Zhang, Matthew D. Piggott

Wind turbine wake modelling is of crucial importance to accurate resource assessment, to layout optimisation, and to the operational control of wind farms. This work proposes a sur…

cs.LG2022★ 5 cited

E2N: Error Estimation Networks for Goal-Oriented Mesh Adaptation

Joseph G. Wallwork, Jingyi Lu, Mingrui Zhang +1

Given a partial differential equation (PDE), goal-oriented error estimation allows us to understand how errors in a diagnostic quantity of interest (QoI), or goal, occur and accumu…

cs.LG2022★ 6 cited

Learning to Estimate and Refine Fluid Motion with Physical Dynamics

Mingrui Zhang, Jianhong Wang, James Tlhomole +1

Extracting information on fluid motion directly from images is challenging. Fluid flow represents a complex dynamic system governed by the Navier-Stokes equations. General optical…

cs.AI2022★ 1 cited

Complex Locomotion Skill Learning via Differentiable Physics

Yu Fang, Jiancheng Liu, Mingrui Zhang +6

Differentiable physics enables efficient gradient-based optimizations of neural network (NN) controllers. However, existing work typically only delivers NN controllers with limited…

cs.LG2022★ 8 cited

M2N: Mesh Movement Networks for PDE Solvers

Wenbin Song, Mingrui Zhang, Joseph G. Wallwork +8

Mainstream numerical Partial Differential Equation (PDE) solvers require discretizing the physical domain using a mesh. Mesh movement methods aim to improve the accuracy of the num…