Dynamic Graph Neural Networks (Dynamic GNNs) have emerged as powerful tools for modeling real-world networks with evolving topologies and node attributes over time. A survey by Professors Zhewei Wei, ...

In this tutorial, we build an advanced, fully autonomous logistics simulation in which multiple smart delivery trucks operate within a dynamic city-wide road network. We design the system so that each ...

Turn your GitHub contribution graph into a playful bubble‑shooter animated SVG you can embed in your README. Generate once or keep it up to date automatically with GitHub Actions. Download or copy ...

Abstract: Dynamic graph representation learning aims to generate low-dimensional latent vector representations of graphs or nodes at various time points from evolving graph datas, which are then used ...

The investment seeks total return. The investment objective of the fund is to seek to achieve total return primarily by managing allocations among a broad range of asset classes, and secondarily by ...

Abstract: This paper focuses on representation learning for dynamic graphs with temporal interactions. A fundamental issue is that both the graph structure and the nodes own their own dynamics, and ...

Loading dag with dynamically mapped task crashes the structure_data endpoint that is used by graph and thus empty page is shown. INFO 127.0.0.1:44476 - "GET /ui ...

Rare is celebrating its 40th anniversary as it was founded back in 1985. "40 years of Rare," said the developer in a statement. "From devoted Rare gamers to single-series stalwarts, we want to show ...

1 School of Resources and Environment, Xizang Agriculture and Animal Husbandry University, Nyingchi, Xizang, China 2 Department of Mechanical Engineering, Taiyuan Institute of Technology, TaiYuan, ...

ABSTRACT: This study proposes a decentralized urban traffic optimization approach by integrating Dijkstra’s algorithm with edge computing. The system models road networks as dynamic graphs, using real ...