no code implementations • 2 Mar 2024 • Yanchao Tan, Hang Lv, Xinyi Huang, Jiawei Zhang, Shiping Wang, Carl Yang
Traditional Graph Neural Networks (GNNs), which are commonly used for modeling attributed graphs, need to be re-trained every time when applied to different graph tasks and datasets.
no code implementations • 28 Nov 2023 • Xiaojing Zhong, Xinyi Huang, Zhonghua Wu, Guosheng Lin, Qingyao Wu
To address this problem, we propose a novel Spatial Alignment and Region-Adaptive normalization method (SARA) in this paper.
no code implementations • 20 Aug 2021 • Suphanut Jamonnak, Ye Zhao, Xinyi Huang, Md Amiruzzaman
The visual study is seamlessly integrated with the geographical environment by combining DL model performance with geospatial visualization techniques.
no code implementations • 9 Dec 2020 • Aozhu Chen, Xinyi Huang, Hailan Lin, Xirong Li
For the first scenario with the references available, we propose two metrics, i. e., WMDRel and CLinRel.
no code implementations • 3 Sep 2020 • Xinyi Huang, Suphanut Jamonnak, Ye Zhao, Boyu Wang, Minh Hoai, Kevin Yager, Wei Xu
Existing interactive visualization tools for deep learning are mostly applied to the training, debugging, and refinement of neural network models working on natural images.
no code implementations • IEEE Transactions on Knowledge and Data Engineering 2020 • Xiaofeng Chen, Hui Li, Jin Li, Qian Wang, Xinyi Huang, Willy Susilo, and Yang Xiang
As a result, it remains an open problem how to construct an efficient (and publicly verifiable) VDB scheme that can support all updating operations regardless of the manner of insertion.
no code implementations • 10 Oct 2019 • Xinyi Huang, Suphanut Jamonnak, Ye Zhao, Boyu Wang, Minh Hoai, Kevin Yager, Wei Xu
This extended abstract presents a visualization system, which is designed for domain scientists to visually understand their deep learning model of extracting multiple attributes in x-ray scattering images.