Jian, Songlei

1. Fascinating Supervisory Signals and Where to Find Them: Deep Anomaly Detection with Scale Learning
   2023/05/25 by Xu, Hongzuo, Wang, Yijie, Wei, Juhui +3 · 6 citations
   #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (cs.LG)
2. Calibrated One-class Classification for Unsupervised Time Series Anomaly Detection
   2022/07/25 by Hongzuo Xu, Xu, Hongzuo, Yijie Wang +9 · 3 citations
   Computer Science · #Anomaly Detection Techniques and Applications #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Network Security and Intrusion Detection #Time Series Analysis and Forecasting
3. Rethinking Class Relations: Absolute-relative Supervised and Unsupervised Few-shot Learning
   2020/01/12 by Hongguang Zhang, Zhang, Hongguang, Piotr Koniusz +7 · 1 citation
   Computer Science · #Computer Vision and Pattern Recognition (cs.CV) #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Human Pose and Action Recognition #Multimodal Machine Learning Applications
4. Hierarchical Adaptive Pooling by Capturing High-order Dependency for Graph Representation Learning
   2021/04/13 by Ning Liu, Liu, Ning, Songlei Jian +9 · 1 citation
   Computer Science · #Advanced Graph Neural Networks #Graph Theory and Algorithms #Recommender Systems and Techniques
5. Gated Cross-Attention Network for Depth Completion
   2023/09/28 by Xiaogang Jia, Songlei Jian, Jia, Xiaogang +7 · 1 citation
   Computer Science · #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Machine Learning and Data Classification
6. RoSAS: Deep Semi-Supervised Anomaly Detection with Contamination-Resilient Continuous Supervision
   2023/07/25 by Hongzuo Xu, Xu, Hongzuo, Yijie Wang +9 · 1 citation
   Computer Science · Medicine · #Anomaly Detection Techniques and Applications #Artificial Intelligence (cs.AI) #Data-Driven Disease Surveillance #FOS: Computer and information sciences #Machine Learning (cs.LG) #Network Security and Intrusion Detection