22 citations · 75 across the 18 of their papers we have counts for
5 papers · 1 filter
Provable Robust Saliency-based Explanations
Chao Chen, Chenghua Guo, Rufeng Chen +5
To foster trust in machine learning models, explanations must be faithful and stable for consistent insights. Existing relevant works rely on the distance for stability as…
Line Graph Contrastive Learning for Link Prediction
Zehua Zhang, Shilin Sun, Guixiang Ma +1
Link prediction tasks focus on predicting possible future connections. Most existing researches measure the likelihood of links by different similarity scores on node pairs and pre…
Memory-Augmented Graph Neural Networks: A Brain-Inspired Review
Guixiang Ma, Vy A. Vo, Theodore Willke +1
We provide a comprehensive review of the existing literature on memory-augmented GNNs. We review these works through the lens of psychology and neuroscience, which has several esta…
Contrastive Brain Network Learning via Hierarchical Signed Graph Pooling Model
Haoteng Tang, Guixiang Ma, Lei Guo +3
Recently brain networks have been widely adopted to study brain dynamics, brain development and brain diseases. Graph representation learning techniques on brain functional network…
End-to-end Mapping in Heterogeneous Systems Using Graph Representation Learning
Yao Xiao, Guixiang Ma, Nesreen K. Ahmed +4
To enable heterogeneous computing systems with autonomous programming and optimization capabilities, we propose a unified, end-to-end, programmable graph representation learning (P…