Search Results for author: Mingrui Zhang

Found 16 papers, 5 papers with code

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

no code implementations24 Nov 2022 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.

Graph Representation Learning

E2N: Error Estimation Networks for Goal-Oriented Mesh Adaptation

no code implementations22 Jul 2022 Joseph G. Wallwork, Jingyi Lu, Mingrui Zhang, Matthew D. Piggott

We demonstrate that this approach is able to obtain the same accuracy with a reduced computational cost, for adaptive mesh test cases related to flow around tidal turbines, which interact via their downstream wakes, and where the overall power output of the farm is taken as the QoI.

Learning to Estimate and Refine Fluid Motion with Physical Dynamics

1 code implementation21 Jun 2022 Mingrui Zhang, Jianhong Wang, James Tlhomole, Matthew D. Piggott

General optical flow methods are typically designed for rigid body motion, and thus struggle if applied to fluid motion estimation directly.

Motion Estimation Optical Flow Estimation

Complex Locomotion Skill Learning via Differentiable Physics

1 code implementation6 Jun 2022 Yu Fang, Jiancheng Liu, Mingrui Zhang, Jiasheng Zhang, Yidong Ma, Minchen Li, Yuanming Hu, Chenfanfu Jiang, Tiantian Liu

Differentiable physics enables efficient gradient-based optimizations of neural network (NN) controllers.

M2N: Mesh Movement Networks for PDE Solvers

1 code implementation24 Apr 2022 Wenbin Song, Mingrui Zhang, Joseph G. Wallwork, Junpeng Gao, Zheng Tian, Fanglei Sun, Matthew D. Piggott, Junqing Chen, Zuoqiang Shi, Xiang Chen, Jun Wang

However, mesh movement methods, such as the Monge-Ampere method, require the solution of auxiliary equations, which can be extremely expensive especially when the mesh is adapted frequently.

Graph Attention

SoftCollage: A Differentiable Probabilistic Tree Generator for Image Collage

1 code implementation CVPR 2022 Jiahao Yu, Li Chen, Mingrui Zhang, Mading Li

While several recent works exploit tree-based algorithm to preserve image content better, all of them resort to hand-crafted adjustment rules to optimize the collage tree structure, leading to the failure of fully exploring the structure space of collage tree.

Aesthetic Photo Collage with Deep Reinforcement Learning

no code implementations19 Oct 2021 Mingrui Zhang, Mading Li, Li Chen, Jiahao Yu

To overcome the lack of training data, we pretrain our deep aesthetic network on a large scale image aesthetic dataset (CPC) for general aesthetic feature extraction and propose an attention fusion module for structural collage feature representation.

reinforcement-learning Reinforcement Learning (RL)

Scalable Projection-Free Optimization

no code implementations7 May 2021 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.

Stochastic Optimization

Unsupervised Learning of Particle Image Velocimetry

1 code implementation28 Jul 2020 Mingrui Zhang, Matthew D. Piggott

Recently, the development of deep learning based methods has inspired new approaches to tackle the PIV problem.

Optical Flow Estimation

More Data Can Expand the Generalization Gap Between Adversarially Robust and Standard Models

no code implementations ICML 2020 Lin Chen, Yifei Min, Mingrui Zhang, Amin Karbasi

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 data, but result in serious and potentially dangerous prediction errors.

One Sample Stochastic Frank-Wolfe

no code implementations10 Oct 2019 Mingrui Zhang, Zebang Shen, Aryan Mokhtari, Hamed Hassani, Amin Karbasi

One of the beauties of the projected gradient descent method lies in its rather simple mechanism and yet stable behavior with inexact, stochastic gradients, which has led to its wide-spread use in many machine learning applications.

Self-Paced Video Data Augmentation with Dynamic Images Generated by Generative Adversarial Networks

no code implementations16 Sep 2019 Yumeng Zhang, Gaoguo Jia, Li Chen, Mingrui Zhang, Junhai Yong

The dynamic image compresses the motion information of video into a still image, removing the interference factors such as the background.

Data Augmentation General Classification +1

Black Box Submodular Maximization: Discrete and Continuous Settings

no code implementations28 Jan 2019 Lin Chen, Mingrui Zhang, Hamed Hassani, Amin Karbasi

In this paper, we consider the problem of black box continuous submodular maximization where we only have access to the function values and no information about the derivatives is provided.

Projection-Free Bandit Convex Optimization

no code implementations18 May 2018 Lin Chen, Mingrui Zhang, Amin Karbasi

In this paper, we propose the first computationally efficient projection-free algorithm for bandit convex optimization (BCO).

Matrix Completion

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