47 citations · 82 across the 16 of their papers we have counts for
4 papers
Discovering COVID-19 Coughing and Breathing Patterns from Unlabeled Data Using Contrastive Learning with Varying Pre-Training Domains
Jinjin Cai, Sudip Vhaduri, Xiao Luo
Rapid discovery of new diseases, such as COVID-19 can enable a timely epidemic response, preventing the large-scale spread and protecting public health. However, limited research e…
Towards Semi-supervised Universal Graph Classification
Xiao Luo, Yusheng Zhao, Yifang Qin +2
Graph neural networks have pushed state-of-the-arts in graph classifications recently. Typically, these methods are studied within the context of supervised end-to-end training, wh…
TGNN: A Joint Semi-supervised Framework for Graph-level Classification
Wei Ju, Xiao Luo, Meng Qu +5
This paper studies semi-supervised graph classification, a crucial task with a wide range of applications in social network analysis and bioinformatics. Recent works typically adop…
Physics-Informed Neural Operator for Fast and Scalable Optical Fiber Channel Modelling in Multi-Span Transmission
Yuchen Song, Danshi Wang, Qirui Fan +3
We propose efficient modelling of optical fiber channel via NLSE-constrained physics-informed neural operator without reference solutions. This method can be easily scalable for di…