97 citations · 191 across the 12 of their papers we have counts for
6 papers · 1 filter
Explaining Imitation Learning through Frames
Boyuan Zheng, Jianlong Zhou, Chunjie Liu +2
As one of the prevalent methods to achieve automation systems, Imitation Learning (IL) presents a promising performance in a wide range of domains. However, despite the considerabl…
GANExplainer: GAN-based Graph Neural Networks Explainer
Yiqiao Li, Jianlong Zhou, Boyuan Zheng +1
With the rapid deployment of graph neural networks (GNNs) based techniques into a wide range of applications such as link prediction, node classification, and graph classification…
A Survey of Explainable Graph Neural Networks: Taxonomy and Evaluation Metrics
Yiqiao Li, Jianlong Zhou, Sunny Verma +1
Graph neural networks (GNNs) have demonstrated a significant boost in prediction performance on graph data. At the same time, the predictions made by these models are often hard to…
Imitation Learning: Progress, Taxonomies and Challenges
Boyuan Zheng, Sunny Verma, Jianlong Zhou +2
Imitation learning aims to extract knowledge from human experts' demonstrations or artificially created agents in order to replicate their behaviors. Its success has been demonstra…
Facilitating Machine Learning Model Comparison and Explanation Through A Radial Visualisation
Jianlong Zhou, Weidong Huang, Fang Chen
Building an effective Machine Learning (ML) model for a data set is a difficult task involving various steps. One of the most important steps is to compare generated substantial am…
Variational Co-embedding Learning for Attributed Network Clustering
Shuiqiao Yang, Sunny Verma, Borui Cai +4
Recent works for attributed network clustering utilize graph convolution to obtain node embeddings and simultaneously perform clustering assignments on the embedding space. It is e…