Zobrazeno 1 - 10
of 42
pro vyhledávání: '"Jin, Fusheng"'
Counting small cohesive subgraphs in a graph is a fundamental operation with numerous applications in graph analysis. Previous studies on cohesive subgraph counting are mainly based on the clique model, which aim to count the number of $k$-cliques in
Externí odkaz:
http://arxiv.org/abs/2405.04823
The construction of online vectorized High-Definition (HD) maps is critical for downstream prediction and planning. Recent efforts have built strong baselines for this task, however, shapes and relations of instances in urban road systems are still u
Externí odkaz:
http://arxiv.org/abs/2312.03341
Graph embedding has become a powerful tool for learning latent representations of nodes in a graph. Despite its superior performance in various graph-based machine learning tasks, serious privacy concerns arise when the graph data contains personal o
Externí odkaz:
http://arxiv.org/abs/2310.11060
Recently, the explanation of neural network models has garnered considerable research attention. In computer vision, CAM (Class Activation Map)-based methods and LRP (Layer-wise Relevance Propagation) method are two common explanation methods. Howeve
Externí odkaz:
http://arxiv.org/abs/2303.09171
Autor:
Jiang, Yutong1 (AUTHOR), Jin, Fusheng1 (AUTHOR) jfs21cn@bit.edu.cn, Chen, Mengnan1 (AUTHOR), Liu, Guoming2 (AUTHOR), Pang, He2 (AUTHOR), Yuan, Ye1 (AUTHOR)
Publikováno v:
GeoInformatica. Oct2024, Vol. 28 Issue 4, p535-557. 23p.
Publikováno v:
In Future Generation Computer Systems May 2023 142:292-300
Publikováno v:
Visual Computer; Sep2024, Vol. 40 Issue 9, p6547-6566, 20p
Publikováno v:
In Information Sciences November 2021 579:814-831
Publikováno v:
In Neurocomputing 7 March 2021 428:352-360
Autor:
Wan, Chuanbing1 (AUTHOR), Jin, Fusheng1 (AUTHOR) jfs21cn@bit.edu.cn, Qiao, Zhuang1 (AUTHOR), Zhang, Weiwei1 (AUTHOR), Yuan, Ye1 (AUTHOR)
Publikováno v:
Neural Computing & Applications. Feb2023, Vol. 35 Issue 5, p3587-3595. 9p.