35 citations · 107 across the 14 of their papers we have counts for
14 papers
LATTE: Label-efficient Incident Phenotyping from Longitudinal Electronic Health Records
Jun Wen, Jue Hou, Clara-Lea Bonzel +14
Electronic health record (EHR) data are increasingly used to support real-world evidence (RWE) studies. Yet its ability to generate reliable RWE is limited by the lack of readily a…
Grid-Centric Traffic Scenario Perception for Autonomous Driving: A Comprehensive Review
Yining Shi, Kun Jiang, Jiusi Li +5
Grid-centric perception is a crucial field for mobile robot perception and navigation. Nonetheless, grid-centric perception is less prevalent than object-centric perception as auto…
Discriminative Radial Domain Adaptation
Zenan Huang, Jun Wen, Siheng Chen +2
Domain adaptation methods reduce domain shift typically by learning domain-invariant features. Most existing methods are built on distribution matching, e.g., adversarial domain ad…
Harnessing electronic health records for real-world evidence
Jue Hou, Rachel Zhao, Jessica Gronsbell +13
While randomized controlled trials (RCTs) are the gold-standard for establishing the efficacy and safety of a medical treatment, real-world evidence (RWE) generated from real-world…
Contrast-reconstruction Representation Learning for Self-supervised Skeleton-based Action Recognition
Peng Wang, Jun Wen, Chenyang Si +2
Skeleton-based action recognition is widely used in varied areas, e.g., surveillance and human-machine interaction. Existing models are mainly learned in a supervised manner, thus…
Semi-Supervised Hypothesis Transfer for Source-Free Domain Adaptation
Ning Ma, Jiajun Bu, Lixian Lu +4
Domain Adaptation has been widely used to deal with the distribution shift in vision, language, multimedia etc. Most domain adaptation methods learn domain-invariant features with…