Zhengping Che
Zhengping Che
DiDi AI Labs, Didi Chuxing
Geverifieerd e-mailadres voor didiglobal.com - Homepage
Geciteerd door
Geciteerd door
Recurrent neural networks for multivariate time series with missing values
Z Che, S Purushotham, K Cho, D Sontag, Y Liu
Scientific reports 8 (1), 6085, 2018
Deep computational phenotyping
Z Che, D Kale, W Li, MT Bahadori, Y Liu
Proceedings of the 21th ACM SIGKDD International Conference on Knowledge …, 2015
Interpretable deep models for ICU outcome prediction
Z Che, S Purushotham, R Khemani, Y Liu
AMIA Annual Symposium Proceedings 2016, 371, 2016
Benchmarking deep learning models on large healthcare datasets
S Purushotham, C Meng, Z Che, Y Liu
Journal of biomedical informatics 83, 112-134, 2018
Distilling knowledge from deep networks with applications to healthcare domain
Z Che, S Purushotham, R Khemani, Y Liu
arXiv preprint arXiv:1512.03542, 2015
Boosting deep learning risk prediction with generative adversarial networks for electronic health records
Z Che, Y Cheng, S Zhai, Z Sun, Y Liu
2017 IEEE International Conference on Data Mining (ICDM), 787-792, 2017
Utilizing machine learning and automated performance metrics to evaluate robot-assisted radical prostatectomy performance and predict outcomes
AJ Hung, J Chen, Z Che, T Nilanon, A Jarc, M Titus, PJ Oh, IS Gill, Y Liu
Journal of endourology 32 (5), 438-444, 2018
Exploiting convolutional neural network for risk prediction with medical feature embedding
Z Che, Y Cheng, Z Sun, Y Liu
arXiv preprint arXiv:1701.07474, 2017
An examination of multivariate time series hashing with applications to health care
DC Kale, D Gong, Z Che, Y Liu, G Medioni, R Wetzel, P Ross
2014 IEEE International Conference on Data Mining, 260-269, 2014
Causal phenotype discovery via deep networks
DC Kale, Z Che, MT Bahadori, W Li, Y Liu, R Wetzel
AMIA Annual Symposium Proceedings 2015, 677, 2015
Deep Learning Solutions for Classifying Patients on Opioid Use
Z Che, J St. Sauver, H Liu, Y Liu
AMIA Annual Symposium Proceedings 2017, 2017
Hierarchical deep generative models for multi-rate multivariate time series
Z Che, S Purushotham, G Li, B Jiang, Y Liu
International Conference on Machine Learning, 784-793, 2018
DECADE: A Deep Metric Learning Model for Multivariate Time Series
Z Che, X He, K Xu, Y Liu
KDD Workshop on Mining and Learning from Time Series (MiLeTS) 2017, 2017
Deep learning solutions to computational phenotyping in health care
Z Che, Y Liu
2017 IEEE International Conference on Data Mining Workshops (ICDMW), 1100-1109, 2017
D-City: A Large-Scale Dashcam Video Dataset of Diverse Traffic Scenarios
Z Che, G Li, T Li, B Jiang, X Shi, X Zhang, Y Lu, G Wu, Y Liu, J Ye
arXiv preprint arXiv:1904.01975, 2019
Computational discovery of physiomes in critically ill children using deep learning
D Kale, Z Che, Y Liu, R Wetzel
DMMI Workshop, AMIA 2014, 2014
DBUS: Human Driving Behavior Understanding System
M Guangyu Li, B Jiang, Z Che, X Shi, M Liu, Y Meng, J Ye, Y Liu
Proceedings of the IEEE International Conference on Computer Vision …, 2019
Time series feature learning with applications to health care
Z Che, S Purushotham, D Kale, W Li, MT Bahadori, R Khemani, Y Liu
Mobile Health, 389-409, 2017
Generative Attention Networks for Multi-Agent Behavioral Modeling
G Li, B Jiang, H Zhu, Z Che, Y Liu
Proceedings of the 34th AAAI Conference on Artificial Intelligence (AAAI), 2020
Deep Learning Models for Temporal Data in Health Care
Z Che
University of Southern California, 2018
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