Zobrazeno 1 - 10
of 71
pro vyhledávání: '"Zhou, Junru"'
Graph neural networks (GNNs) have achieved remarkable success in a variety of machine learning tasks over graph data. Existing GNNs usually rely on message passing, i.e., computing node representations by gathering information from the neighborhood,
Externí odkaz:
http://arxiv.org/abs/2410.09737
Autor:
Zhou, Junru, Zhang, Muhan
The ability of graph neural networks (GNNs) to count homomorphisms has recently been proposed as a practical and fine-grained measure of their expressive power. Although several existing works have investigated the homomorphism counting power of cert
Externí odkaz:
http://arxiv.org/abs/2410.03517
The ability of graph neural networks (GNNs) to count certain graph substructures, especially cycles, is important for the success of GNNs on a wide range of tasks. It has been recently used as a popular metric for evaluating the expressive power of G
Externí odkaz:
http://arxiv.org/abs/2309.04941
We investigate the enhancement of graph neural networks' (GNNs) representation power through their ability in substructure counting. Recent advances have seen the adoption of subgraph GNNs, which partition an input graph into numerous subgraphs, subs
Externí odkaz:
http://arxiv.org/abs/2303.10576
Autor:
Gui, Yaohui, Huang, Changping, Zhou, Junru, Zhang, Ze, Wang, Jin, Kang, Xiaoyan, Huang, Wenjiang, Lv, Xin, Zhang, Lifu
Publikováno v:
In Industrial Crops & Products 1 November 2024 219
Autor:
Zhang, Fan, Chen, Chen, Zhou, Junru, Zhu, Qun, Chen, Wenjun, Zhang, Qiuzhuo, Long, Mingce, Chen, Chao
Publikováno v:
In Separation and Purification Technology 24 December 2024 351
Autor:
Zheng, Chuanrong, Guan, Jiani, Zhang, Fan, Zhou, Junru, Wang, Dandan, Zhao, Yuting, Zhang, Pengyan, Yan, Mengqin, Chen, Wenjun, Zhu, Qun, He, Jinyi, Liao, Fengtiao, Zhang, Xikui, Long, Mingce, Chen, Chao
Publikováno v:
In Applied Catalysis B: Environment and Energy 15 December 2024 359
Autor:
Zhang, Fan, Chen, Chen, Zhou, Junru, Zheng, Chuanrong, Zhu, Qun, Peng, Feng, Chen, Wenjun, Zhang, Qiuzhuo, Long, Mingce, Chen, Chao
Publikováno v:
In Separation and Purification Technology 20 March 2024 332
Constituent and dependency parsing, the two classic forms of syntactic parsing, have been found to benefit from joint training and decoding under a uniform formalism, Head-driven Phrase Structure Grammar (HPSG). However, decoding this unified grammar
Externí odkaz:
http://arxiv.org/abs/2105.09835
Understanding human language is one of the key themes of artificial intelligence. For language representation, the capacity of effectively modeling the linguistic knowledge from the detail-riddled and lengthy texts and getting rid of the noises is es
Externí odkaz:
http://arxiv.org/abs/2012.13915