26 citations · 64 across the 13 of their papers we have counts for
13 papers
Tokenized Graph Transformer with Neighborhood Augmentation for Node Classification in Large Graphs
Jinsong Chen, Chang Liu, Kaiyuan Gao +2
Graph Transformers, emerging as a new architecture for graph representation learning, suffer from the quadratic complexity on the number of nodes when handling large graphs. To thi…
LaCon: Late-Constraint Diffusion for Steerable Guided Image Synthesis
Chang Liu, Rui Li, Kaidong Zhang +2
Diffusion models have demonstrated impressive abilities in generating photo-realistic and creative images. To offer more controllability for the generation process, existing studie…
Towards Effective Adversarial Textured 3D Meshes on Physical Face Recognition
Xiao Yang, Chang Liu, Longlong Xu +5
Face recognition is a prevailing authentication solution in numerous biometric applications. Physical adversarial attacks, as an important surrogate, can identify the weaknesses of…
A structured input-output approach to characterizing optimal perturbations in wall-bounded shear flows
Chang Liu, Yu Shuai, Aishwarya Rath +1
This work builds upon recent work exploiting the notion of structured singular values to capture nonlinear interactions in the analysis of wall-bounded shear flows. In this context…
A Comprehensive Study on Robustness of Image Classification Models: Benchmarking and Rethinking
Chang Liu, Yinpeng Dong, Wenzhao Xiang +7
The robustness of deep neural networks is usually lacking under adversarial examples, common corruptions, and distribution shifts, which becomes an important research problem in th…
Invertible Rescaling Network and Its Extensions
Mingqing Xiao, Shuxin Zheng, Chang Liu +2
Image rescaling is a commonly used bidirectional operation, which first downscales high-resolution images to fit various display screens or to be storage- and bandwidth-friendly, a…
Tensor Recovery Based on A Novel Non-convex Function Minimax Logarithmic Concave Penalty Function
Hongbing Zhang, Xinyi Liu, Chang Liu +3
Non-convex relaxation methods have been widely used in tensor recovery problems, and compared with convex relaxation methods, can achieve better recovery results. In this paper, a…
An Empirical Study of Graphormer on Large-Scale Molecular Modeling Datasets
Yu Shi, Shuxin Zheng, Guolin Ke +7
This technical note describes the recent updates of Graphormer, including architecture design modifications, and the adaption to 3D molecular dynamics simulation. The "Graphormer-V…
Benchmarking Graphormer on Large-Scale Molecular Modeling Datasets
Yu Shi, Shuxin Zheng, Guolin Ke +7
This technical note describes the recent updates of Graphormer, including architecture design modifications, and the adaption to 3D molecular dynamics simulation. With these simple…
Invertible Image Rescaling
Mingqing Xiao, Shuxin Zheng, Chang Liu +6
High-resolution digital images are usually downscaled to fit various display screens or save the cost of storage and bandwidth, meanwhile the post-upscaling is adpoted to recover t…
Straight-Through Estimator as Projected Wasserstein Gradient Flow
Pengyu Cheng, Chang Liu, Chunyuan Li +3
The Straight-Through (ST) estimator is a widely used technique for back-propagating gradients through discrete random variables. However, this effective method lacks theoretical ju…
Received Signal Strength Based Wireless Source Localization with Inaccurate Anchor Position
Yang Liu, Guojun Han, Yonghua Wang +2
Received signal strength (RSS)-based wireless localization is easy to implement at low cost. In practice,exact positions of anchors may not be available. This paper focuses on dete…
Understanding MCMC Dynamics as Flows on the Wasserstein Space
Chang Liu, Jingwei Zhuo, Jun Zhu
It is known that the Langevin dynamics used in MCMC is the gradient flow of the KL divergence on the Wasserstein space, which helps convergence analysis and inspires recent particl…