Journal articles on the topic 'Neural Network Embeddings'
Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles
Consult the top 50 journal articles for your research on the topic 'Neural Network Embeddings.'
Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.
You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.
Browse journal articles on a wide variety of disciplines and organise your bibliography correctly.
Che, Feihu, Dawei Zhang, Jianhua Tao, Mingyue Niu, and Bocheng Zhao. "ParamE: Regarding Neural Network Parameters as Relation Embeddings for Knowledge Graph Completion." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 03 (April 3, 2020): 2774–81. http://dx.doi.org/10.1609/aaai.v34i03.5665.
Huang, Junjie, Huawei Shen, Liang Hou, and Xueqi Cheng. "SDGNN: Learning Node Representation for Signed Directed Networks." Proceedings of the AAAI Conference on Artificial Intelligence 35, no. 1 (May 18, 2021): 196–203. http://dx.doi.org/10.1609/aaai.v35i1.16093.
Srinidhi, K., T. L.S Tejaswi, CH Rama Rupesh Kumar, and I. Sai Siva Charan. "An Advanced Sentiment Embeddings with Applications to Sentiment Based Result Analysis." International Journal of Engineering & Technology 7, no. 2.32 (May 31, 2018): 393. http://dx.doi.org/10.14419/ijet.v7i2.32.15721.
Armandpour, Mohammadreza, Patrick Ding, Jianhua Huang, and Xia Hu. "Robust Negative Sampling for Network Embedding." Proceedings of the AAAI Conference on Artificial Intelligence 33 (July 17, 2019): 3191–98. http://dx.doi.org/10.1609/aaai.v33i01.33013191.
Kamath, S., K. G. Karibasappa, Anvitha Reddy, Arati M. Kallur, B. B. Priyanka, and B. P. Bhagya. "Improving the Relation Classification Using Convolutional Neural Network." IOP Conference Series: Materials Science and Engineering 1187, no. 1 (September 1, 2021): 012004. http://dx.doi.org/10.1088/1757-899x/1187/1/012004.
Gu, Haishuo, Jinguang Sui, and Peng Chen. "Graph Representation Learning for Street-Level Crime Prediction." ISPRS International Journal of Geo-Information 13, no. 7 (July 1, 2024): 229. http://dx.doi.org/10.3390/ijgi13070229.
Zhang, Lei, Feng Qian, Jie Chen, and Shu Zhao. "An Unsupervised Rapid Network Alignment Framework via Network Coarsening." Mathematics 11, no. 3 (January 21, 2023): 573. http://dx.doi.org/10.3390/math11030573.
Truică, Ciprian-Octavian, Elena-Simona Apostol, Maria-Luiza Șerban, and Adrian Paschke. "Topic-Based Document-Level Sentiment Analysis Using Contextual Cues." Mathematics 9, no. 21 (October 27, 2021): 2722. http://dx.doi.org/10.3390/math9212722.
Jang, Youngjin, and Harksoo Kim. "Reliable Classification of FAQs with Spelling Errors Using an Encoder-Decoder Neural Network in Korean." Applied Sciences 9, no. 22 (November 7, 2019): 4758. http://dx.doi.org/10.3390/app9224758.
Guo, Lei, Haoran Jiang, Xiyu Liu, and Changming Xing. "Network Embedding-Aware Point-of-Interest Recommendation in Location-Based Social Networks." Complexity 2019 (November 4, 2019): 1–18. http://dx.doi.org/10.1155/2019/3574194.
Nguyen, Van Quan, Tien Nguyen Anh, and Hyung-Jeong Yang. "Real-time event detection using recurrent neural network in social sensors." International Journal of Distributed Sensor Networks 15, no. 6 (June 2019): 155014771985649. http://dx.doi.org/10.1177/1550147719856492.
Jadon, Anil Kumar, and Suresh Kumar. "Enhancing emotion detection with synergistic combination of word embeddings and convolutional neural networks." Indonesian Journal of Electrical Engineering and Computer Science 35, no. 3 (September 1, 2024): 1933. http://dx.doi.org/10.11591/ijeecs.v35.i3.pp1933-1941.
Altuntas, Volkan. "NodeVector: A Novel Network Node Vectorization with Graph Analysis and Deep Learning." Applied Sciences 14, no. 2 (January 16, 2024): 775. http://dx.doi.org/10.3390/app14020775.
Jbene, Mourad, Smail Tigani, Saadane Rachid, and Abdellah Chehri. "Deep Neural Network and Boosting Based Hybrid Quality Ranking for e-Commerce Product Search." Big Data and Cognitive Computing 5, no. 3 (August 13, 2021): 35. http://dx.doi.org/10.3390/bdcc5030035.
Popov, Alexander. "Neural Network Models for Word Sense Disambiguation: An Overview." Cybernetics and Information Technologies 18, no. 1 (March 1, 2018): 139–51. http://dx.doi.org/10.2478/cait-2018-0012.
Hu, Ganglin, and Jun Pang. "Relation-Aware Weighted Embedding for Heterogeneous Graphs." Information Technology and Control 52, no. 1 (March 28, 2023): 199–214. http://dx.doi.org/10.5755/j01.itc.52.1.32390.
Bui-Thi, Danh, Emmanuel Rivière, Pieter Meysman, and Kris Laukens. "Predicting compound-protein interaction using hierarchical graph convolutional networks." PLOS ONE 17, no. 7 (July 21, 2022): e0258628. http://dx.doi.org/10.1371/journal.pone.0258628.
Wang, Bin, Yu Chen, Jinfang Sheng, and Zhengkun He. "Attributed Graph Embedding Based on Attention with Cluster." Mathematics 10, no. 23 (December 1, 2022): 4563. http://dx.doi.org/10.3390/math10234563.
Eyharabide, Victoria, Imad Eddine Ibrahim Bekkouch, and Nicolae Dragoș Constantin. "Knowledge Graph Embedding-Based Domain Adaptation for Musical Instrument Recognition." Computers 10, no. 8 (August 3, 2021): 94. http://dx.doi.org/10.3390/computers10080094.
Boldakov, V. "Emotional Speech Synthesis with Emotion Embeddings." Herald of the Siberian State University of Telecommunications and Informatics, no. 4 (December 18, 2021): 23–31. http://dx.doi.org/10.55648/1998-6920-2021-15-4-23-31.
Ota, Kosuke, Keiichiro Shirai, Hidetoshi Miyao, and Minoru Maruyama. "Multimodal Analogy-Based Image Retrieval by Improving Semantic Embeddings." Journal of Advanced Computational Intelligence and Intelligent Informatics 26, no. 6 (November 20, 2022): 995–1003. http://dx.doi.org/10.20965/jaciii.2022.p0995.
Takase, Sho, Jun Suzuki, and Masaaki Nagata. "Character n-Gram Embeddings to Improve RNN Language Models." Proceedings of the AAAI Conference on Artificial Intelligence 33 (July 17, 2019): 5074–82. http://dx.doi.org/10.1609/aaai.v33i01.33015074.
Nguyen, Andre T., Fred Lu, Gary Lopez Munoz, Edward Raff, Charles Nicholas, and James Holt. "Out of Distribution Data Detection Using Dropout Bayesian Neural Networks." Proceedings of the AAAI Conference on Artificial Intelligence 36, no. 7 (June 28, 2022): 7877–85. http://dx.doi.org/10.1609/aaai.v36i7.20757.
P. Bhopale, Bhopale, and Ashish Tiwari. "LEVERAGING NEURAL NETWORK PHRASE EMBEDDING MODEL FOR QUERY REFORMULATION IN AD-HOC BIOMEDICAL INFORMATION RETRIEVAL." Malaysian Journal of Computer Science 34, no. 2 (April 30, 2021): 151–70. http://dx.doi.org/10.22452/mjcs.vol34no2.2.
Gao, Yan, Yandong Wang, Patrick Wang, and Lei Gu. "Medical Named Entity Extraction from Chinese Resident Admit Notes Using Character and Word Attention-Enhanced Neural Network." International Journal of Environmental Research and Public Health 17, no. 5 (March 2, 2020): 1614. http://dx.doi.org/10.3390/ijerph17051614.
Ng, Michael K., Hanrui Wu, and Andy Yip. "Stability and Generalization of Hypergraph Collaborative Networks." Machine Intelligence Research 21, no. 1 (January 15, 2024): 184–96. http://dx.doi.org/10.1007/s11633-022-1397-1.
Wu, Xueyi, Yuanyuan Xu, Wenjie Zhang, and Ying Zhang. "Billion-Scale Bipartite Graph Embedding: A Global-Local Induced Approach." Proceedings of the VLDB Endowment 17, no. 2 (October 2023): 175–83. http://dx.doi.org/10.14778/3626292.3626300.
Hagad, Juan Lorenzo, Tsukasa Kimura, Ken-ichi Fukui, and Masayuki Numao. "Learning Subject-Generalized Topographical EEG Embeddings Using Deep Variational Autoencoders and Domain-Adversarial Regularization." Sensors 21, no. 5 (March 4, 2021): 1792. http://dx.doi.org/10.3390/s21051792.
Kim, Harang, and Hyun Min Song. "Lightweight IDS Framework Using Word Embeddings for In-Vehicle Network Security." Journal of Wireless Mobile Networks, Ubiquitous Computing, and Dependable Applications 15, no. 2 (June 29, 2022): 1–13. http://dx.doi.org/10.58346/jowua.2024.i2.001.
Li, Wenli, and Gang Wu. "One-shot Based Knowledge Graph Embedded Neural Architecture Search Algorithm." Frontiers in Computing and Intelligent Systems 3, no. 3 (May 4, 2023): 1–5. http://dx.doi.org/10.54097/fcis.v3i3.7982.
Zhang, Kainan, Zhipeng Cai, and Daehee Seo. "Privacy-Preserving Federated Graph Neural Network Learning on Non-IID Graph Data." Wireless Communications and Mobile Computing 2023 (February 3, 2023): 1–13. http://dx.doi.org/10.1155/2023/8545101.
Peng, Hao, Qing Ke, Ceren Budak, Daniel M. Romero, and Yong-Yeol Ahn. "Neural embeddings of scholarly periodicals reveal complex disciplinary organizations." Science Advances 7, no. 17 (April 2021): eabb9004. http://dx.doi.org/10.1126/sciadv.abb9004.
Özkaya Eren, Ayşegül, and Mustafa Sert. "Audio Captioning with Composition of Acoustic and Semantic Information." International Journal of Semantic Computing 15, no. 02 (June 2021): 143–60. http://dx.doi.org/10.1142/s1793351x21400018.
Ye, Yutong, Xiang Lian, and Mingsong Chen. "Efficient Exact Subgraph Matching via GNN-Based Path Dominance Embedding." Proceedings of the VLDB Endowment 17, no. 7 (March 2024): 1628–41. http://dx.doi.org/10.14778/3654621.3654630.
Croce, Danilo, Daniele Rossini, and Roberto Basili. "Neural embeddings: accurate and readable inferences based on semantic kernels." Natural Language Engineering 25, no. 4 (July 2019): 519–41. http://dx.doi.org/10.1017/s1351324919000238.
Zhou, Silin, Jing Li, Hao Wang, Shuo Shang, and Peng Han. "GRLSTM: Trajectory Similarity Computation with Graph-Based Residual LSTM." Proceedings of the AAAI Conference on Artificial Intelligence 37, no. 4 (June 26, 2023): 4972–80. http://dx.doi.org/10.1609/aaai.v37i4.25624.
Tzougas, George, and Konstantin Kutzkov. "Enhancing Logistic Regression Using Neural Networks for Classification in Actuarial Learning." Algorithms 16, no. 2 (February 9, 2023): 99. http://dx.doi.org/10.3390/a16020099.
Chang, Zhihao, Linzhu Yu, Yanchao Xu, and Wentao Hu. "Neural Embeddings for kNN Search in Biological Sequence." Proceedings of the AAAI Conference on Artificial Intelligence 38, no. 1 (March 24, 2024): 38–45. http://dx.doi.org/10.1609/aaai.v38i1.27753.
Xu, You-Wei, Hong-Jun Zhang, Kai Cheng, Xiang-Lin Liao, Zi-Xuan Zhang, and Yun-Bo Li. "Knowledge graph embedding with entity attributes using hypergraph neural networks." Intelligent Data Analysis 26, no. 4 (July 11, 2022): 959–75. http://dx.doi.org/10.3233/ida-216007.
Zhong, Fengzhe, Yan Liu, Lian Liu, Guangsheng Zhang, and Shunran Duan. "DEDGCN: Dual Evolving Dynamic Graph Convolutional Network." Security and Communication Networks 2022 (May 10, 2022): 1–11. http://dx.doi.org/10.1155/2022/6945397.
Zhang, Yuanpeng, Jingye Guan, Haobo Wang, Kaiming Li, Ying Luo, and Qun Zhang. "Generalized Zero-Shot Space Target Recognition Based on Global-Local Visual Feature Embedding Network." Remote Sensing 15, no. 21 (October 28, 2023): 5156. http://dx.doi.org/10.3390/rs15215156.
E., Koshel. "Нейронно-мережевий підхід до неперервного вкладення одновимірних потоків даних для аналізу часових рядів в реальному часі." System technologies 2, no. 151 (April 17, 2024): 92–101. http://dx.doi.org/10.34185/1562-9945-2-151-2024-08.
Levy, Omer, Yoav Goldberg, and Ido Dagan. "Improving Distributional Similarity with Lessons Learned from Word Embeddings." Transactions of the Association for Computational Linguistics 3 (December 2015): 211–25. http://dx.doi.org/10.1162/tacl_a_00134.
Wang, Yu, Ke Wang, Fengjuan Gao, and Linzhang Wang. "Learning semantic program embeddings with graph interval neural network." Proceedings of the ACM on Programming Languages 4, OOPSLA (November 13, 2020): 1–27. http://dx.doi.org/10.1145/3428205.
Eliyahu Sason, Yackov Lubarsky, Alexei Gaissinski, Eli Kravchik, and Pavel Kisilev. "Oracle-based data generation for highly efficient digital twin network training." ITU Journal on Future and Evolving Technologies 4, no. 3 (September 8, 2023): 472–84. http://dx.doi.org/10.52953/aweu6345.
Hu, Shengze, Weixin Zeng, Pengfei Zhang, and Jiuyang Tang. "Neural Graph Similarity Computation with Contrastive Learning." Applied Sciences 12, no. 15 (July 29, 2022): 7668. http://dx.doi.org/10.3390/app12157668.
Sun, Xia, Ke Dong, Long Ma, Richard Sutcliffe, Feijuan He, Sushing Chen, and Jun Feng. "Drug-Drug Interaction Extraction via Recurrent Hybrid Convolutional Neural Networks with an Improved Focal Loss." Entropy 21, no. 1 (January 8, 2019): 37. http://dx.doi.org/10.3390/e21010037.
Si, Yuqi, Jingqi Wang, Hua Xu, and Kirk Roberts. "Enhancing clinical concept extraction with contextual embeddings." Journal of the American Medical Informatics Association 26, no. 11 (July 2, 2019): 1297–304. http://dx.doi.org/10.1093/jamia/ocz096.
Zhuang, Chengxu, Siming Yan, Aran Nayebi, Martin Schrimpf, Michael C. Frank, James J. DiCarlo, and Daniel L. K. Yamins. "Unsupervised neural network models of the ventral visual stream." Proceedings of the National Academy of Sciences 118, no. 3 (January 11, 2021): e2014196118. http://dx.doi.org/10.1073/pnas.2014196118.
Wang, Chaoyi. "Collaborative filtering method based on graph neural network." Applied and Computational Engineering 6, no. 1 (June 14, 2023): 1288–94. http://dx.doi.org/10.54254/2755-2721/6/20230710.