20 citations · 58 across the 6 of their papers we have counts for
11 papers
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…
Aesthetic Photo Collage with Deep Reinforcement Learning
Mingrui Zhang, Mading Li, Li Chen +1
Photo collage aims to automatically arrange multiple photos on a given canvas with high aesthetic quality. Existing methods are based mainly on handcrafted feature optimization, wh…
Scalable Projection-Free Optimization
Mingrui Zhang
As a projection-free algorithm, Frank-Wolfe (FW) method, also known as conditional gradient, has recently received considerable attention in the machine learning community. In this…
Unsupervised Learning of Particle Image Velocimetry
Mingrui Zhang, Matthew D. Piggott
Particle Image Velocimetry (PIV) is a classical flow estimation problem which is widely considered and utilised, especially as a diagnostic tool in experimental fluid dynamics and…
More Data Can Expand the Generalization Gap Between Adversarially Robust and Standard Models
Lin Chen, Yifei Min, Mingrui Zhang +1
Despite remarkable success in practice, modern machine learning models have been found to be susceptible to adversarial attacks that make human-imperceptible perturbations to the d…
Online Continuous Submodular Maximization: From Full-Information to Bandit Feedback
Mingrui Zhang, Lin Chen, Hamed Hassani +1
In this paper, we propose three online algorithms for submodular maximisation. The first one, Mono-Frank-Wolfe, reduces the number of per-function gradient evaluations from $T^{1/2…