13 citations · 22 across the 10 of their papers we have counts for
10 papers
Scalable Volt-VAR Optimization using RLlib-IMPALA Framework: A Reinforcement Learning Approach
Alaa Selim, Yanzhu Ye, Junbo Zhao +1
In the rapidly evolving domain of electrical power systems, the Volt-VAR optimization (VVO) is increasingly critical, especially with the burgeoning integration of renewable energy…
Energy-based Automated Model Evaluation
Ru Peng, Heming Zou, Haobo Wang +3
The conventional evaluation protocols on machine learning models rely heavily on a labeled, i.i.d-assumed testing dataset, which is not often present in real world applications. Th…
Revisiting the Knowledge Injection Frameworks
Peng Fu, Yiming Zhang, Haobo Wang +2
In recent years, large language models (LLMs), such as GPTs, have attained great impact worldwide. However, how to adapt these LLMs to better suit the vertical domain-specific task…
Deep Reinforcement Learning-Enabled Adaptive Forecasting-Aided State Estimation in Distribution Systems with Multi-Source Multi-Rate Data
Ying Zhang, Junbo Zhao, Di Shi +1
Distribution system state estimation (DSSE) is paramount for effective state monitoring and control. However, stochastic outputs of renewables and asynchronous streaming of multi-r…
Resilient Model-Free Asymmetric Bipartite Consensus for Nonlinear Multi-Agent Systems against DoS Attacks
Yi Zhang, Yichao Wang, Junbo Zhao +1
In this letter, we study an unified resilient asymmetric bipartite consensus (URABC) problem for nonlinear multi-agent systems with both cooperative and antagonistic interactions u…
ChatDB: Augmenting LLMs with Databases as Their Symbolic Memory
Chenxu Hu, Jie Fu, Chenzhuang Du +3
Large language models (LLMs) with memory are computationally universal. However, mainstream LLMs are not taking full advantage of memory, and the designs are heavily influenced by…