252 citations · 689 across the 37 of their papers we have counts for
5 papers · 1 filter
Physics-informed Evolutionary Strategy based Control for Mitigating Delayed Voltage Recovery
Yan Du, Qiuhua Huang, Renke Huang +4
In this work we propose a novel data-driven, real-time power system voltage control method based on the physics-informed guided meta evolutionary strategy (ES). The main objective…
Robot Learning from Randomized Simulations: A Review
Fabio Muratore, Fabio Ramos, Greg Turk +3
The rise of deep learning has caused a paradigm shift in robotics research, favoring methods that require large amounts of data. Unfortunately, it is prohibitively expensive to gen…
Learning from Counterfactual Links for Link Prediction
Tong Zhao, Gang Liu, Daheng Wang +2
Learning to predict missing links is important for many graph-based applications. Existing methods were designed to learn the association between observed graph structure and exist…
Validating Label Consistency in NER Data Annotation
Qingkai Zeng, Mengxia Yu, Wenhao Yu +2
Data annotation plays a crucial role in ensuring your named entity recognition (NER) projects are trained with the right information to learn from. Producing the most accurate labe…
Learning and Fast Adaptation for Grid Emergency Control via Deep Meta Reinforcement Learning
Renke Huang, Yujiao Chen, Tianzhixi Yin +6
As power systems are undergoing a significant transformation with more uncertainties, less inertia and closer to operation limits, there is increasing risk of large outages. Thus,…