2 citations · 4 across the 5 of their papers we have counts for
5 papers
Interaction Pattern Disentangling for Multi-Agent Reinforcement Learning
Shunyu Liu, Jie Song, Yihe Zhou +4
Deep cooperative multi-agent reinforcement learning has demonstrated its remarkable success over a wide spectrum of complex control tasks. However, recent advances in multi-agent l…
Ask-AC: An Initiative Advisor-in-the-Loop Actor-Critic Framework
Shunyu Liu, Kaixuan Chen, Na Yu +3
Despite the promising results achieved, state-of-the-art interactive reinforcement learning schemes rely on passively receiving supervision signals from advisor experts, in the for…
Distribution-Aware Graph Representation Learning for Transient Stability Assessment of Power System
Kaixuan Chen, Shunyu Liu, Na Yu +5
The real-time transient stability assessment (TSA) plays a critical role in the secure operation of the power system. Although the classic numerical integration method, \textit{i.e…
Imbalanced Sample Generation and Evaluation for Power System Transient Stability Using CTGAN
Gengshi Han, Shunyu Liu, Kaixuan Chen +3
Although deep learning has achieved impressive advances in transient stability assessment of power systems, the insufficient and imbalanced samples still trap the training effect o…
Distribution Knowledge Embedding for Graph Pooling
Kaixuan Chen, Jie Song, Shunyu Liu +4
Graph-level representation learning is the pivotal step for downstream tasks that operate on the whole graph. The most common approach to this problem heretofore is graph pooling,…