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ORCIDChenguang Wang 0006
Person information
- affiliation: Delft University of Technology, Department of Electrical Sustainable Engineering, The Netherlands
Other persons with the same name
- Chenguang Wang (aka: Chen-guang Wang) — disambiguation page
- Chenguang Wang 0001 — Washington University in St. Louis, Department of Computer Science and Engineering, MO, USA (and 4 more)
- Chenguang Wang 0002
![[0000-0002-9009-5263]](https://dblp.uni-trier.de./img/orcid-mark.12x12.png "0000-0002-9009-5263")
— China Three Gorges University, College of Economics and Management, Yichang, China - Chenguang Wang 0003 — Tsinghua University, Department of Computer Science and Technology, Beijing, China
- Chenguang Wang 0004 — Harbin Medical University, Department of Bioinformatics, China
- Chenguang Wang 0005 — Harbin University of Science and Technology, College of Electrical and Electronic Engineering, China
- Chenguang Wang 0007 — North University of China, Taiyuan, China
- Chenguang Wang 0008 — China University of Geosciences, Wuhan, China
- Chenguang Wang 0009 — University of Electronic Science and Technology of China, Chengdu, China
- Chenguang Wang 0010 — Xi'an University of Technology, Xi'an, China
- Chenguang Wang 0011 — Chinese University of Hong Kong, Shenzhen, Shenzhen, China
- Chenguang Wang 0012 — Stony Brook University, Stony Brook, NY, USA
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2020 – today
- 2024
[j1]Chenguang Wang, Simon H. Tindemans, Peter Palensky:
Improved Anomaly Detection and Localization Using Whitening-Enhanced Autoencoders. IEEE Trans. Ind. Informatics 20(1): 659-668 (2024)- [i7]Weijie Xia, Chenguang Wang, Peter Palensky, Pedro P. Vergara:
A Flow-Based Model for Conditional and Probabilistic Electricity Consumption Profile Generation and Prediction. CoRR abs/2405.02180 (2024) - [i6]Weijie Xia, Gao Peng, Chenguang Wang, Peter Palensky, Eric J. Pauwels, Pedro P. Vergara:
An Efficient and Explainable Transformer-Based Few-Shot Learning for Modeling Electricity Consumption Profiles Across Thousands of Domains. CoRR abs/2408.08399 (2024) - 2023
- [b1]Chenguang Wang:
Anomaly Detection and Synthetic Data Generation for Power Systems Using Autoencoder Neural Networks. Delft University of Technology, Netherlands, 2023 - [i5]Chenguang Wang, Ensieh Sharifnia, Simon H. Tindemans, Peter Palensky:
Targeted Analysis of High-Risk States Using an Oriented Variational Autoencoder. CoRR abs/2303.11410 (2023) - 2022
- [c2]Chenguang Wang, Simon H. Tindemans, Peter Palensky:
Generating Contextual Load Profiles Using a Conditional Variational Autoencoder. ISGT-Europe 2022: 1-6 - [i4]Chenguang Wang, Simon H. Tindemans, Peter Palensky:
Generating Contextual Load Profiles Using a Conditional Variational Autoencoder. CoRR abs/2209.04056 (2022) - 2021
- [i3]Chenguang Wang, Ensieh Sharifnia, Zhi Gao, Simon H. Tindemans, Peter Palensky:
Generating Multivariate Load States Using a Conditional Variational Autoencoder. CoRR abs/2110.11435 (2021) - 2020
- [c1]Chenguang Wang, Kaikai Pan, Simon H. Tindemans, Peter Palensky:
Training Strategies for Autoencoder-based Detection of False Data Injection Attacks. ISGT-Europe 2020: 1-5 - [i2]Chenguang Wang, Simon H. Tindemans, Kaikai Pan, Peter Palensky:
Detection of False Data Injection Attacks Using the Autoencoder Approach. CoRR abs/2003.02229 (2020) - [i1]Chenguang Wang, Kaikai Pan, Simon H. Tindemans, Peter Palensky:
Training Strategies for Autoencoder-based Detection of False Data Injection Attacks. CoRR abs/2005.07158 (2020)
Coauthor Index
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