103 citations · 159 across the 5 of their papers we have counts for
6 papers
XFake: Explainable Fake News Detector with Visualizations
Fan Yang, Shiva K. Pentyala, Sina Mohseni +6
In this demo paper, we present the XFake system, an explainable fake news detector that assists end-users to identify news credibility. To effectively detect and interpret the fake…
Graph Representation Learning via Hard and Channel-Wise Attention Networks
Hongyang Gao, Shuiwang Ji
Attention operators have been widely applied in various fields, including computer vision, natural language processing, and network embedding learning. Attention operators on graph…
Graph U-Nets
Hongyang Gao, Shuiwang Ji
We consider the problem of representation learning for graph data. Convolutional neural networks can naturally operate on images, but have significant challenges in dealing with gr…
Dense Transformer Networks
Jun Li, Yongjun Chen, Lei Cai +2
The key idea of current deep learning methods for dense prediction is to apply a model on a regular patch centered on each pixel to make pixel-wise predictions. These methods are l…
Multi-Stage Variational Auto-Encoders for Coarse-to-Fine Image Generation
Lei Cai, Hongyang Gao, Shuiwang Ji
Variational auto-encoder (VAE) is a powerful unsupervised learning framework for image generation. One drawback of VAE is that it generates blurry images due to its Gaussianity ass…
Pixel Deconvolutional Networks
Hongyang Gao, Hao Yuan, Zhengyang Wang +1
Deconvolutional layers have been widely used in a variety of deep models for up-sampling, including encoder-decoder networks for semantic segmentation and deep generative models fo…