arXiv admin note: text overlap with arXiv:2401.13784
*[RRT Based Optimal Trajectory Generation with Linear Temporal Logic Specifications under Kinodynamic Constraints](http://arxiv.org/abs/2411.06219v1)**
Scale invariance in node classification is demonstrated and applied in graph transformation to develop ScaleNet, which achieves state-of-the-art performance on both homophilic and heterophilic directed graphs
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Time Series
6 pag...
6 pages, 3 figures, IEEE Big Data 2024
Added...
Added funding acknowledgment and author bios
New r...
New revision added a space between "for" and "Time-Series" in the title
Will ...
Will be published as part of "Cemracs Proceedings 2023" (status: accepted)
Trajectory
Accep...
Accepted and presented at ECCV 2024 2nd Workshop on Vision-Centric Autonomous Driving (VCAD) on September 30, 2024. 13 pages, 5 figures
Accep...
Accepted at the IEEE International Conference on Systems, Man, and Cybernetics 2024
In Vi...
In Vietnamese language, in the 25th National Conference on Electronics, Communications and Information Technology (REV-ECIT 2022), Hanoi, Vietnam
Submi...
Submitted; 42 pages, comments are welcome
arXiv...
arXiv admin note: text overlap with arXiv:2401.13784
Graph Neural Networks
Accep...
Accepted by IEEE JSAC NGAT
9 pag...
9 pages, 2 figures, 5 tables
Accep...
Accepted to DATE 2025
Scale...
Scale invariance in node classification is demonstrated and applied in graph transformation to develop ScaleNet, which achieves state-of-the-art performance on both homophilic and heterophilic directed graphs
Under...
Under review as a conference paper at ICLR 2025