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Found 5 papers, 1 papers with code
ToupleGDD: A Fine-Designed Solution of Influence Maximization by Deep Reinforcement Learning
Aiming at selecting a small subset of nodes with maximum influence on networks, the Influence Maximization (IM) problem has been extensively studied.
Graph Representation Learning for Popularity Prediction Problem: A Survey
In this paper, we present a comprehensive review for existing works using GRL methods for popularity prediction problem, and categorize related literatures into two big classes, according to their mainly used model and techniques: embedding-based methods and deep learning methods.
Urban traffic dynamic rerouting framework: A DRL-based model with fog-cloud architecture
To address this question, this study proposes a two-stage model that combines GAQ (Graph Attention Network - Deep Q Learning) and EBkSP (Entropy Based k Shortest Path) using a fog-cloud architecture, to reroute vehicles in a dynamic urban environment and therefore to improve travel efficiency in terms of travel speed.
Development and testing of an image transformer for explainable autonomous driving systems
The results demonstrate the efficacy of our proposed model as it exhibits superior performance (in terms of correct prediction of actions and explanations) compared to the benchmark model by a significant margin with lower computational cost.
A Random Algorithm for Profit Maximization with Multiple Adoptions in Online Social Networks
Through "word of mouth" effects, information or product adoption could spread from some influential individuals to millions of users in social networks.
Social and Information Networks
