5 citations · 6 across the 5 of their papers we have counts for
5 papers
Graph Evidential Learning for Anomaly Detection
Chunyu Wei, Wenji Hu, Xingjia Hao +4
Graph anomaly detection faces significant challenges due to the scarcity of reliable anomaly-labeled datasets, driving the development of unsupervised methods. Graph autoencoders (…
Rethink Deep Learning with Invariance in Data Representation
Shuren Qi, Fei Wang, Tieyong Zeng +1
Integrating invariance into data representations is a principled design in intelligent systems and web applications. Representations play a fundamental role, where systems and appl…
Towards Clinical AI Fairness: Filling Gaps in the Puzzle
Mingxuan Liu, Yilin Ning, Salinelat Teixayavong +16
The ethical integration of Artificial Intelligence (AI) in healthcare necessitates addressing fairness-a concept that is highly context-specific across medical fields. Extensive st…
Towards clinical AI fairness: A translational perspective
Mingxuan Liu, Yilin Ning, Salinelat Teixayavong +12
Artificial intelligence (AI) has demonstrated the ability to extract insights from data, but the issue of fairness remains a concern in high-stakes fields such as healthcare. Despi…
Neural Network Gaussian Processes by Increasing Depth
Shao-Qun Zhang, Fei Wang, Feng-Lei Fan
Recent years have witnessed an increasing interest in the correspondence between infinitely wide networks and Gaussian processes. Despite the effectiveness and elegance of the curr…