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Dan Li (李丹)
Dan Li (李丹)
PhD, EEE @ NTU; Associate Professor, SSE @ SYSU
Verified email at e.ntu.edu.sg - Homepage
Title
Cited by
Cited by
Year
MAD-GAN: Multivariate anomaly detection for time series data with generative adversarial networks
D Li, D Chen, B Jin, L Shi, J Goh, SK Ng
International Conference on Artificial Neural Networks, 703-716, 2019
9002019
Anomaly Detection with Generative Adversarial Networks for Multivariate Time Series
D Li, D Chen, J Goh, S Ng
arXiv preprint arXiv:1809.04758, 2018
3162018
A data-driven strategy for detection and diagnosis of building chiller faults using linear discriminant analysis
D Li, G Hu, CJ Spanos
Energy and Buildings 128, 519-529, 2016
1672016
Fault detection and diagnosis for building cooling system with a tree-structured learning method
D Li, Y Zhou, G Hu, CJ Spanos
Energy and Buildings 127, 540-551, 2016
1042016
Design Automation for Smart Building Systems
R Jia, B Jin, M Jin, Y Zhou, IC Konstantakopoulos, H Zou, J Kim, D Li, ...
Proceedings of the IEEE 106 (9), 1680-1699, 2018
982018
Optimal sensor configuration and feature selection for AHU fault detection and diagnosis
D Li, Y Zhou, G Hu, CJ Spanos
IEEE Transactions on Industrial Informatics 13 (3), 1369-1380, 2016
572016
Handling Incomplete Sensor Measurements in Fault Detection and Diagnosis for Building HVAC Systems
D Li, Y Zhou, G Hu, CJ Spanos
IEEE Transactions on Automation Science and Engineering 17 (2), 833-846, 2019
392019
Detecting and diagnosing incipient building faults using uncertainty information from deep neural networks
B Jin, D Li, S Srinivasan, SK Ng, K Poolla, A Sangiovanni-Vincentelli
2019 IEEE International Conference on Prognostics and Health Management …, 2019
372019
A one-class support vector machine calibration method for time series change point detection
B Jin, Y Chen, D Li, K Poolla, A Sangiovanni-Vincentelli
2019 IEEE International Conference on Prognostics and Health Management …, 2019
342019
Identifying Unseen Faults for Smart Buildings by Incorporating Expert Knowledge With Data
D Li, Y Zhou, G Hu, CJ Spanos
IEEE Transactions on Automation Science and Engineering 16 (3), 1412-1425, 2018
282018
Driver attention prediction based on convolution and transformers
C Gou, Y Zhou, D Li
The Journal of Supercomputing 78 (6), 8268-8284, 2022
222022
Learning optimization friendly comfort model for hvac model predictive control
Y Zhou, D Li, CJ Spanos
2015 IEEE International Conference on Data Mining Workshop (ICDMW), 430-439, 2015
132015
MAD-SGCN: Multivariate Anomaly Detection with Self-learning Graph Convolutional Networks
P Qi, D Li, SK Ng
2022 IEEE 38th International Conference on Data Engineering (ICDE), 1232-1244, 2022
102022
Fusing system configuration information for building cooling plant fault detection and severity level identification
D Li, Y Zhou, G Hu, CJ Spanos
2016 IEEE International Conference on Automation Science and Engineering …, 2016
92016
Optimal training and efficient model selection for parameterized large margin learning
Y Zhou, JY Baek, D Li, CJ Spanos
Pacific-Asia Conference on Knowledge Discovery and Data Mining, 52-64, 2016
82016
Electrocardiogram classification and visual diagnosis of atrial fibrillation with DenseECG
D Chen, D Li, X Xu, R Yang, SK Ng
arXiv preprint arXiv:2101.07535, 2021
7*2021
VC-GAN: classifying vessel types by maritime trajectories using generative adversarial networks
D Li, H Liu, SK Ng
2020 IEEE 32nd International Conference on Tools with Artificial …, 2020
32020
Fault detection and diagnosis for chillers and AHUs of building ACMV systems
D Li
PhD thesis, 2017
32017
CB-GAN: Generate Sensitive Data with a Convolutional Bidirectional Generative Adversarial Networks
R Hu, D Li, SK Ng, Z Zheng
International Conference on Database Systems for Advanced Applications, 159-174, 2023
22023
Fault Detection and Diagnosis of Air Handling Units Based On Adversarial Multi-task Learning
J Tan, D Li, Z Zheng, SK Ng
2023 IEEE International Conference on Data Mining Workshops (ICDMW), 89-98, 2023
2023
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