GitHub

DeFoG: Discrete Flow Matching for Graph Generation

A PyTorch implementation of the DeFoG model for training and sampling discrete graph flows. (Please update to the latest commit. Recent fixes have been applied.) Working with directed graphs? Consider ...
IEEE

A Graph Deep Reinforcement Learning Traffic Signal Control for Multiple Intersections Considering Missing Data

Abstract: Efficient traffic signal control (TSC) for multiple intersections is an important way to solve traffic congestion. With the development of deep reinforcement learning (DRL), an increasing ...
GitHub

CGBridge: Bridging Code Graphs and Large Language Models for Better Structure-Aware Code Understanding

CGBridge is a novel framework designed to enhance the code understanding capabilities of Large Language Models (LLMs) by integrating rich structural information from code graphs. Our approach follows ...
IEEE

Control Mode Switching-Enabled Physics- Guided Multiagent Graph Learning for Real-Time AC/DC Power Flow

Abstract: Existing ac/dc power flow computations necessitate sequential convergence-oriented trial-and-error under various dc control modes, rising computational ...
Frontiers

Resilience optimization and dynamic stability defense in active distribution networks under extreme disasters: a graph learning and cooperative control approach

1 Guangdong Power Grid Corporation Foshan Power Supply Bureau, Foshan, China 2 Electric Power Research Institute of China Southern Power Grid, Guangzhou, Guangdong, China Introduction: The escalating ...