activity
20162022
most citedSLEEPNET: Automated Sleep Staging System via Deep Learning

103 citations · 519 across the 37 of their papers we have counts for

collaborators

59 papers

math.NA20214 cited

MTC: Multiresolution Tensor Completion from Partial and Coarse Observations

Chaoqi Yang, Navjot Singh, Cao Xiao +3

Existing tensor completion formulation mostly relies on partial observations from a single tensor. However, tensors extracted from real-world data are often more complex due to: (i…

cs.LG20213 cited

Locally Valid and Discriminative Prediction Intervals for Deep Learning Models

Zhen Lin, Shubhendu Trivedi, Jimeng Sun

Crucial for building trust in deep learning models for critical real-world applications is efficient and theoretically sound uncertainty quantification, a task that continues to be…

cs.LG2021

Multi-version Tensor Completion for Time-delayed Spatio-temporal Data

Cheng Qian, Nikos Kargas, Cao Xiao +3

Real-world spatio-temporal data is often incomplete or inaccurate due to various data loading delays. For example, a location-disease-time tensor of case counts can have multiple d…

cs.LG2021

Change Matters: Medication Change Prediction with Recurrent Residual Networks

Chaoqi Yang, Cao Xiao, Lucas Glass +1

Deep learning is revolutionizing predictive healthcare, including recommending medications to patients with complex health conditions. Existing approaches focus on predicting all m…

cs.LG2021

Machine Learning Applications for Therapeutic Tasks with Genomics Data

Kexin Huang, Cao Xiao, Lucas M. Glass +3

Thanks to the increasing availability of genomics and other biomedical data, many machine learning approaches have been proposed for a wide range of therapeutic discovery and devel…

cs.LG2021

SCRIB: Set-classifier with Class-specific Risk Bounds for Blackbox Models

Zhen Lin, Cao Xiao, Lucas Glass +2

Despite deep learning (DL) success in classification problems, DL classifiers do not provide a sound mechanism to decide when to refrain from predicting. Recent works tried to cont…