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Abstract: Graph neural networks (GNNs) have demonstrated significant success in solving real-world problems using both static and dynamic graph data. While static graphs remain constant, dynamic ...

Explore the power of interactive physics visualizations with animated graphs using VPython and GlowScript for dynamic simulations! This guide demonstrates how to create real-time animated graphs that ...

ABSTRACT: Foot-and-Mouth Disease (FMD) remains a critical threat to global livestock industries, causing severe economic losses and trade restrictions. This paper proposes a novel application of ...

Notes on sandboxing untrusted Python Python’s dynamism makes it difficult to run untrusted code safely. Developer Mohamed Diallo discusses some ways that Python interpreters could be made easier to ...

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, ...

When considering Miguel Arzabe’s bold, woven works, it’s unsurprising that he begins by painting two abstract pieces. Vibrant fields of acrylic spread across his canvases before they’re sliced into ...

@inproceedings{steinke2025curbosg, author={Steinke, Tim and Büchner, Martin and Vödisch, Niclas and Valada, Abhinav}, booktitle={2025 IEEE/RSJ International Conference on Intelligent Robots and ...

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 ...

Qingdao Institute of Software, College of Computer Science and Technology, Shandong Key Laboratory of Intelligent Oil & Gas Industrial Software, China University of Petroleum (East China), Qingdao ...