Efficient preconditioning of the linearized Navier−Stokes equations 著者: Elman, H, Wathen, A, Silvester, D, Elman, H, Kay, D

Benchmarking Graph Transformers Toward Scalability for Large Graphs 著者: Lim, Katherine S.

“…By adding GraphGPS-inspired message-passing neural network (MPNN) layers to a modified version of the Spectral Attention Network (SAN) and performing hyperparameter tuning, we built a GT architecture that performs comparably to GraphGPS on the node classification task on the Cora and CiteSeer datasets. Compared to the modified version of SAN that we started with, our architecture is faster to train and evaluate, and also obtains higher node classification accuracies on the Cora and CiteSeer datasets. …”
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OverCite : a cooperative digital research library 著者: Stribling, Jeremy

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Bet-GAT: An Efficient Centrality-Based Graph Attention Model for Semi-Supervised Node Classification 著者: Atul Kumar Verma, Rahul Saxena, Mahipal Jadeja, Vikrant Bhateja, Jerry Chun-Wei Lin

“…Moreover, to the best of our knowledge, the results obtained for Citeseer, Wiki- CS, and Amazon Computer datasets are the best compared to all the existing node classification methods.…”
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A Relationship-Aware Feature Update Method for Enhanced Graph-Based Neural Networks 著者: Conggui Huang

“…Experimental results demonstrate that, with an external graph, the method achieves superior accuracy and faster learning rates on the Cora and Citeseer datasets. Additionally, it outperforms state-of-the-art baseline methods in mean average precision, rank-1 accuracy, and learning rate on the Market-1501, DukeMTMC, VeRi-776, and MSMT17 datasets. …”
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SOCIO-PSYCHOLOGICAL ASPECTS OF SEX EDUCATION 著者: Venera Telzhan

“…Relevant articles and materials for analysis were collected from Science Direct, Google Scholar, Elsevier, Citeseer, PubMed, Web of Science, Scopus search engines after applying inclusion and screening criteria. …”
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Citation counting tool for online academic databases 著者: Zhao, Chen

“…However, such key is contorted by many problems including missing, erroneous or irrelevant citation records among major online academic databases, such like Web of Science (WoS), Scopus, Google Scholar, CiteSeer and so on. In addition, many computer scientists believe that there is a traditional bias toward journals compared to conference papers and their authors, as stated by Bjorn De Sutter and Aaron Van Den Oord in their research paper “To be or not to be cited in computer science.” …”
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GRNN: Graph-Retraining Neural Network for Semi-Supervised Node Classification 著者: Jianhe Li, Suohai Fan

“…The experiments show that GRNN achieves high accuracy in the standard citation network datasets, including Cora, Citeseer, and PubMed, which proves the effectiveness of GRNN in semi-supervised node classification.…”
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Graph Adaptive Attention Network with Cross-Entropy 著者: Zhao Chen

“…The experiments show that classification accuracy achieves outstanding performances on Cora, Citeseer, and Pubmed datasets.…”
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Geometry-V-Sub: An Efficient Graph Attention Network Struct Based Model for Node Classification 著者: Zhengyu Lyu, Wulamu Aziguli, Dezheng Zhang

“…The number of parameters is only 13.05–16.26% of baseline model, and the accuracy of Cora, Citeseer and PubMed is max to 80.4%, 68% and 81.8%, respectively. …”
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Balancing Memory Efficiency and Accuracy in Spectral-Based Graph Transformers 著者: Ho, Kelly

“…We evaluate our model on standard node classification benchmarks: Cora, Citeseer, and Chameleon. Unlike SAN, which runs out of memory, our memory-efficient graph transformer can be run on these benchmarks. …”
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Batch virtual adversarial training for graph convolutional networks 著者: Zhijie Deng, Yinpeng Dong, Jun Zhu

“…Extensive experiments on three citation network datasets Cora, Citeseer and Pubmed and a knowledge graph dataset Nell validate the efficacy of the proposed method in semi-supervised node classification tasks.…”
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Exploiting Weak Ties in Incomplete Network Datasets Using Simplified Graph Convolutional Neural Networks 著者: Neda H. Bidoki, Alexander V. Mantzaris, Gita Sukthankar

“…This is done by applying the methodological framework of the Simplified Graph Convolutional Neural Network (SGC) to two academic publication datasets: Cora and Citeseer. The performance of SGC is compared to the original Graph Convolutional Network (GCN) framework. …”
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Hashtag Recommendation Methods for Twitter and Sina Weibo: A Review 著者: Areej Alsini, Du Q. Huynh, Amitava Datta

“…In this paper, we search for articles related to our research between 2010 and 2020 from CiteSeer, IEEE Xplore, Springer and ACM digital libraries. …”
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Performance investigation of domestic refrigerator using pure hydrocarbons and blends of hydrocarbons as refrigerants 著者: Sattar, M.A., Saidur, Rahman, Masjuki, Haji Hassan

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Adaptive Graph Convolution Using Heat Kernel for Attributed Graph Clustering 著者: Danyang Zhu, Shudong Chen, Xiuhui Ma, Rong Du

“…The clustering results of AGCHK on three benchmark datasets—Cora, Citeseer, and Pubmed—are all more than 1% higher than the current advanced model AGC, and 12% on the Wiki dataset especially, which obtains a state-of-the-art result in the task of attributed graph clustering.…”
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EGNAS: Efficient Graph Neural Architecture Search Through Evolutionary Algorithm 著者: Younkyung Jwa, Chang Wook Ahn, Man-Je Kim

“…Our experimental results demonstrate that EGNAS outperforms state-of-the-art methods in node classification tasks on the Cora, Citeseer, and PubMed datasets while maintaining a high degree of computational efficiency. …”
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Knowledge graph learning algorithm based on deep convolutional networks 著者: Yuzhong Zhou, Zhengping Lin, Jie Lin, Yuliang Yang, Jiahao Shi

“…We evaluate the effectiveness of KGLA-DCNN on two benchmark datasets, Cora and Citeseer, renowned for their challenging node classification tasks. …”
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ESA-GCN: An Enhanced Graph-Based Node Classification Method for Class Imbalance Using ENN-SMOTE Sampling and an Attention Mechanism 著者: Liying Zhang, Haihang Sun

“…Experiments conducted on three public datasets (Cora, Citeseer, and PubMed) demonstrate that the ESA-GCN has achieved significant results in class imbalance node classification tasks.…”
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Ensemble graph auto-encoders for clustering and link prediction 著者: Chengxin Xie, Jingui Huang, Yongjiang Shi, Hui Pang, Liting Gao, Xiumei Wen

“…The model’s performance is evaluated using three publicly available datasets (Cora, Citeseer, and PubMed), indicating its effectiveness through multiple experiments. …”
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