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