[1]
Weibo Liu, Zidong Wang, Xiaohui Liu, Nianyin Zeng, Yurong Liu, Fuad E. Alsaadi, "A survey of deep neural network architectures and their applications," Neurocomputing, vol. 234, pp. 11 - 26, 2017.
[2]
Qingchen Zhang, Laurence T. Yang, Zhikui Chen, Peng Li , "A survey on deep learning for big data," Information Fusion, vol. 42, pp. 146-157, 2018.
[3]
Alex Krizhevsky, Ilya Sutskever, Geoffrey E. Hinton, "ImageNet Classification with Deep Convolutional Neural Networks," in 26th Conference on Neural Information Processing Systems, 2012.
[4]
Weitao Wan, Yuanyi Zhong, Tianpeng Li, Jiansheng Chen, "Rethinking Feature Distribution for Loss Functions in Image Classification," in 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2018.
[5]
Jonathan Long, Evan Shelhamer, Trevor Darrell, "Fully convolutional networks for semantic segmentation," in 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Boston, 2015.
[6]
Maria Papadomanolaki, Maria Vakalopoulou, Konstantinos Karantzalos, "A Novel Object-Based Deep Learning Framework for Semantic Segmentation of Very High-Resolution Remote Sensing Data: Comparison with Convolutional and Fully Convolutional Networks," Remote Sensing, vol. 11, no. 6, 2019.
[7]
Long Chen, Hanwang Zhang, Jun Xiao, Liqiang Nie, Jian Shao, Wei Liu, Tat-Seng Chua, "SCA-CNN: Spatial and Channel-wise Attention in Convolutional Networks for Image Captioning," in 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017.
[8]
Jyoti Aneja, Aditya Deshpande, Alexander Schwing, "Convolutional Image Captioning," in 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018.
[9]
Sepp Hochreiter, Jürgen Schmidhuber, "Long Short-Term Memory," Neural Computation, vol. 9, no. 8, pp. 1735-1780, 1997.
[10]
Duyu Tang, Bing Qin, Ting Liu, "Document Modeling with Gated Recurrent Neural Network for Sentiment Classification," in 2015 Conference on Empirical Methods in Natural Language Processing, 2015.
[11]
Yukun Ma, Haiyun Peng, Erik Cambria, "Targeted Aspect-Based Sentiment Analysis via Embedding Commonsense Knowledge into an Attentive LSTM," in 32 AAAI Conference on Artificial Intelligence, New Orleans, 2018.
[12]
Shujie Liu, Nan Yang, Mu Li, Ming Zhou, "A Recursive Recurrent Neural Network for Statistical Machine Translation," in 52nd Annual Meeting of the Association for Computational Linguistics, Baltimore, 2014.
[13]
Jinsong Su. Shan Wu, Deyi Xiong, Yaojie Lu, Xianpei Han, Biao Zhang, "Variational Recurrent Neural Machine Translation," in 32 AAAI Conference on Artificial Intelligence, New Orleans, 2018.
[14]
Caiming Xiong, Stephen Merity, Richard Socher, "Dynamic Memory Networks for Visual and Textual Question Answering," in 33nd International Conference on Machine Learning, 2016.
[15]
Yankai Lin, Haozhe Ji, Zhiyuan Liu, Maosong Sun, "Denoising Distantly Supervised Open-Domain Question Answering," in 56th Annual Meeting of the Association for Computational Linguistics, Melbourne, 2018.
[16]
Edward T Bullmore, Olaf Sporns, "Complex brain networks: Graph theoretical analysis of structural and functional systems," Nature Reviews Neuroscience, vol. 10, no. 3, 2009.
[17]
Meysam Mirzaei, Aminollah Mahabadi, "Hybrid Anomaly Detection Method Using Community Detection in Graph and Feature Selection," Journal of Electronical & Cyber Defence, vol. 8, no. 1, pp. 17-24, 2020. (In Persian)
[18]
James Atwood, Don Towsley, "Diffusion-Convolutional Neural Networks," in 30th Conference on Neural Information Processing Systems, 2016.
[19]
Qimai Li, Zhichao Han, Xiao-ming Wu, "Deeper Insights Into Graph Convolutional Networks for Semi-Supervised Learning," in 32nd AAAI Conference on Artificial Intelligence, New Orleans, 2018.
[20]
Muhan Zhang, Yixin Chen, "Link Prediction Based on Graph Neural Networks," in 32nd Conference on Neural Information Processing Systems, 2018.
[21]
Xiaojun Xu, Chang Liu, Qian Feng, Heng Yin, Le Song, Dawn Song, "Neural Network-based Graph Embedding for Cross-Platform Binary Code Similarity Detection," in 2017 ACM SIGSAC Conference on Computer and Communications Security, 2017.
[22]
Mathias Niepert, Mohamed Ahmed, Konstantin Kutzkov, "Learning Convolutional Neural Networks for Graphs," in 33rd International Conference on Machine Learning, 2016.
[23]
Muhan Zhang, Zhicheng Cui, Marion Neumann, Yixin Chen, "An End-to-End Deep Learning Architecture for Graph Classification," in 32nd AAAI Conference on Artificial Intelligence, 2018.
[24]
Przemyslaw Kazienko , Tomasz Kajdanowicz, "Label-dependent node classification in the network," Neurocomputing, vol. 75, no. 1, pp. 199 - 209, 2012.
[25]
HongYun Cai, Vincent W. Zheng, Kevin Chen-Chuan Chang, "A Comprehensive Survey of Graph Embedding: Problems, Techniques, and Applications," IEEE Transactions on Knowledge and Data Engineering, vol. 30, no. 9, pp. 1616 - 1637, 2018.
[26]
Qimai Li, Zhichao Han, Xiao-Ming Wu, "Deeper Insights into Graph Convolutional Networks for Semi-Supervised Learning," in 32 AAAI Conference on Artificial Intelligence, Menlo Park, 2018.
[27]
Guohao Li, Matthias Müller, Guocheng Qian, Itzel C. Delgadillo, Abdulellah Abualshour, Ali Thabet, Bernard Ghanem, "DeepGCNs: Making GCNs Go as Deep as CNNs," in 2019 IEEE/CVF International Conference on Computer Vision (ICCV), Seoul, 2019.
[28]
Bryan Perozzi, Rami Al-Rfou, Steven Skiena, "DeepWalk: Online Learning of Social Representations," in 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, New York, 2014.
[29]
Aditya Grover, Jure Leskovec, "node2vec: Scalable Feature Learning for Networks," in 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2016.
[30]
Jian Tang, Meng Qu, Mingzhe Wang, Ming Zhang, Jun Yan, Qiaozhu Mei, "LINE: Large-scale Information Network Embedding," in 24th International Conference onWorld Wide Web, Montreal, 2015.
[31]
Thomas N. Kipf, Max Welling, "Semi-Supervised Classification with Graph Convolutional Networks," in 4th International Conference on Learning Representations, 2016.
[32]
Petar Veličković, Guillem Cucurull, Arantxa Casanova, Adriana Romero, Pietro Liò, Yoshua Bengio, "Graph Attention Networks," in 5th International Conference on Learning Representations, 2017.
[33]
William L. Hamilton, Rex Ying, Jure Leskovec, "Inductive Representation Learning on Large Graphs," in 31st Conference on Neural Information Processing Systems, 2017.
[34]
Chao Li, Li Wang, Shiwen Sun, Chengyi Xia, "Identification of influential spreaders based on classified neighbors in real-world complex networks," Applied Mathematics and Computation, vol. 320, pp. 512-523, 2017.
[35]
Etienne Gael Tajeuna, Mohamed Bouguessa, Shengrui Wang, "Modeling and Predicting Community Structure Changes in Time-Evolving Social Networks," IEEE Transactions on Knowledge and Data Engineering, vol. 31, no. 6, pp. 1166 - 1180, 2019.
[36] Yizhou Sun, Yintao Yu, Jiawei Han, "Ranking-based Clustering of Heterogeneous Information Networks with star Network Schema," in 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, New York, 2009.
[37]
Vincenzo Nicosia, Vito Latora, "Measuring and modelling correlations in multiplex networks," PHYSICAL REVIEW E, 2015.
[38]
Zhishuang Wang, Quantong Guo, Shiwen Sun, Chengyi Xia, "The impact of awareness diffusion on SIR-like epidemics in multiplex networks," Applied Mathematics and Computation, vol. 349, pp. 134-147, 2019.
[39] Shunxin Xiao, Shiping Wang, Yuanfei Dai, Wenzhong Guo, "Graph neural networks in node classification: survey and evaluation," Machine Vision and Applications, vol. 33, no. 1, 2022.
[40] Jiawei Zhang, Haopeng Zhang, Congying Xia, Li Sun, "Graph-Bert: Only Attention is Needed for Learning Graph Representations," 2020.