Добірка наукової літератури з теми "Hypergraph-structure"
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Статті в журналах з теми "Hypergraph-structure"
Xu, Jinhuan, Liang Xiao, and Jingxiang Yang. "Unified Low-Rank Subspace Clustering with Dynamic Hypergraph for Hyperspectral Image." Remote Sensing 13, no. 7 (April 2, 2021): 1372. http://dx.doi.org/10.3390/rs13071372.
Повний текст джерелаFeng, Yifan, Haoxuan You, Zizhao Zhang, Rongrong Ji, and Yue Gao. "Hypergraph Neural Networks." Proceedings of the AAAI Conference on Artificial Intelligence 33 (July 17, 2019): 3558–65. http://dx.doi.org/10.1609/aaai.v33i01.33013558.
Повний текст джерелаLiu, Jian, Dong Chen, Jingyan Li, and Jie Wu. "Neighborhood hypergraph model for topological data analysis." Computational and Mathematical Biophysics 10, no. 1 (January 1, 2022): 262–80. http://dx.doi.org/10.1515/cmb-2022-0142.
Повний текст джерелаYang, Zhe, Liangkui Xu, and Lei Zhao. "Multimodal Feature Fusion Based Hypergraph Learning Model." Computational Intelligence and Neuroscience 2022 (May 16, 2022): 1–13. http://dx.doi.org/10.1155/2022/9073652.
Повний текст джерелаMahmood Shuker, Faiza. "Improved Blockchain Network Performance using Hypergraph Structure." Journal of Engineering and Applied Sciences 14, no. 2 (November 20, 2019): 5579–84. http://dx.doi.org/10.36478/jeasci.2019.5579.5584.
Повний текст джерелаPeng, Hao, Cheng Qian, Dandan Zhao, Ming Zhong, Jianmin Han, and Wei Wang. "Targeting attack hypergraph networks." Chaos: An Interdisciplinary Journal of Nonlinear Science 32, no. 7 (July 2022): 073121. http://dx.doi.org/10.1063/5.0090626.
Повний текст джерелаXu, Xixia, Qi Zou, and Xue Lin. "Adaptive Hypergraph Neural Network for Multi-Person Pose Estimation." Proceedings of the AAAI Conference on Artificial Intelligence 36, no. 3 (June 28, 2022): 2955–63. http://dx.doi.org/10.1609/aaai.v36i3.20201.
Повний текст джерелаHuang, Yuan, Liping Wang, Xueying Wang, and Wei An. "Joint Probabilistic Hypergraph Matching Labeled Multi-Bernoulli Filter for Rigid Target Tracking." Applied Sciences 10, no. 1 (December 20, 2019): 99. http://dx.doi.org/10.3390/app10010099.
Повний текст джерелаKosian, David A., and Leon A. Petrosyan. "Two-Level Cooperative Game on Hypergraph." Contributions to Game Theory and Management 14 (2021): 227–35. http://dx.doi.org/10.21638/11701/spbu31.2021.17.
Повний текст джерелаSiriwong, Pinkaew, and Ratinan Boonklurb. "k-Zero-Divisor and Ideal-Based k-Zero-Divisor Hypergraphs of Some Commutative Rings." Symmetry 13, no. 11 (October 20, 2021): 1980. http://dx.doi.org/10.3390/sym13111980.
Повний текст джерелаДисертації з теми "Hypergraph-structure"
Datta, Sagnik. "Fully bayesian structure learning of bayesian networks and their hypergraph extensions." Thesis, Compiègne, 2016. http://www.theses.fr/2016COMP2283.
Повний текст джерелаIn this thesis, I address the important problem of the determination of the structure of complex networks, with the widely used class of Bayesian network models as a concrete vehicle of my ideas. The structure of a Bayesian network represents a set of conditional independence relations that hold in the domain. Learning the structure of the Bayesian network model that represents a domain can reveal insights into its underlying causal structure. Moreover, it can also be used for prediction of quantities that are difficult, expensive, or unethical to measure such as the probability of cancer based on other quantities that are easier to obtain. The contributions of this thesis include (A) a software developed in C language for structure learning of Bayesian networks; (B) introduction a new jumping kernel in the Metropolis-Hasting algorithm for faster sampling of networks (C) extending the notion of Bayesian networks to structures involving loops and (D) a software developed specifically to learn cyclic structures. Our primary objective is structure learning and thus the graph structure is our parameter of interest. We intend not to perform estimation of the parameters involved in the mathematical models
Sharma, Govind. "Hypergraph Network Models: Learning, Prediction, and Representation in the Presence of Higher-Order Relations." Thesis, 2020. https://etd.iisc.ac.in/handle/2005/4781.
Повний текст джерелаЧастини книг з теми "Hypergraph-structure"
Dai, Qionghai, and Yue Gao. "Hypergraph Structure Evolution." In Artificial Intelligence: Foundations, Theory, and Algorithms, 101–20. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-0185-2_6.
Повний текст джерелаDai, Qionghai, and Yue Gao. "Hypergraph Computation Paradigms." In Artificial Intelligence: Foundations, Theory, and Algorithms, 41–47. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-0185-2_3.
Повний текст джерелаDai, Qionghai, and Yue Gao. "Hypergraph Modeling." In Artificial Intelligence: Foundations, Theory, and Algorithms, 49–71. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-0185-2_4.
Повний текст джерелаDai, Qionghai, and Yue Gao. "Neural Networks on Hypergraph." In Artificial Intelligence: Foundations, Theory, and Algorithms, 121–43. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-0185-2_7.
Повний текст джерелаDai, Qionghai, and Yue Gao. "Mathematical Foundations of Hypergraph." In Artificial Intelligence: Foundations, Theory, and Algorithms, 19–40. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-0185-2_2.
Повний текст джерелаDai, Qionghai, and Yue Gao. "The DeepHypergraph Library." In Artificial Intelligence: Foundations, Theory, and Algorithms, 237–40. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-0185-2_12.
Повний текст джерелаDai, Qionghai, and Yue Gao. "Typical Hypergraph Computation Tasks." In Artificial Intelligence: Foundations, Theory, and Algorithms, 73–99. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-0185-2_5.
Повний текст джерелаDai, Qionghai, and Yue Gao. "Hypergraph Computation for Medical and Biological Applications." In Artificial Intelligence: Foundations, Theory, and Algorithms, 191–221. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-0185-2_10.
Повний текст джерелаKosian, David A., and Leon A. Petrosyan. "New Characteristic Function for Cooperative Games with Hypergraph Communication Structure." In Static & Dynamic Game Theory: Foundations & Applications, 87–98. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-51941-4_7.
Повний текст джерелаMunshi, Shiladitya, Ayan Chakraborty, and Debajyoti Mukhopadhyay. "Constraint Driven Stratification of RDF with Hypergraph Graph (HG(2)) Data Structure." In Communications in Computer and Information Science, 167–80. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-36321-4_15.
Повний текст джерелаТези доповідей конференцій з теми "Hypergraph-structure"
Cai, Derun, Moxian Song, Chenxi Sun, Baofeng Zhang, Shenda Hong, and Hongyan Li. "Hypergraph Structure Learning for Hypergraph Neural Networks." In Thirty-First International Joint Conference on Artificial Intelligence {IJCAI-22}. California: International Joint Conferences on Artificial Intelligence Organization, 2022. http://dx.doi.org/10.24963/ijcai.2022/267.
Повний текст джерелаZhang, Zizhao, Haojie Lin, and Yue Gao. "Dynamic Hypergraph Structure Learning." In Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}. California: International Joint Conferences on Artificial Intelligence Organization, 2018. http://dx.doi.org/10.24963/ijcai.2018/439.
Повний текст джерелаChang, Hyung Jin, Tobias Fischer, Maxime Petit, Martina Zambelli, and Yiannis Demiris. "Kinematic Structure Correspondences via Hypergraph Matching." In 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, 2016. http://dx.doi.org/10.1109/cvpr.2016.457.
Повний текст джерелаJiang, Jianwen, Yuxuan Wei, Yifan Feng, Jingxuan Cao, and Yue Gao. "Dynamic Hypergraph Neural Networks." In Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}. California: International Joint Conferences on Artificial Intelligence Organization, 2019. http://dx.doi.org/10.24963/ijcai.2019/366.
Повний текст джерелаZhou, Peng, Zongqian Wu, Xiangxiang Zeng, Guoqiu Wen, Junbo Ma, and Xiaofeng Zhu. "Totally Dynamic Hypergraph Neural Networks." In Thirty-Second International Joint Conference on Artificial Intelligence {IJCAI-23}. California: International Joint Conferences on Artificial Intelligence Organization, 2023. http://dx.doi.org/10.24963/ijcai.2023/275.
Повний текст джерелаKok, Stanley, and Pedro Domingos. "Learning Markov logic network structure via hypergraph lifting." In the 26th Annual International Conference. New York, New York, USA: ACM Press, 2009. http://dx.doi.org/10.1145/1553374.1553440.
Повний текст джерелаMunshi, Shiladitya, Ayan Chakraborty, and Debajyoti Mukhopadhyay. "Theories of Hypergraph-Graph (HG(2)) Data Structure." In 2013 International Conference on Cloud & Ubiquitous Computing & Emerging Technologies (CUBE). IEEE, 2013. http://dx.doi.org/10.1109/cube.2013.45.
Повний текст джерелаLi, Shengkun, Dawei Du, Longyin Wen, Ming-Ching Chang, and Siwei Lyu. "Hybrid structure hypergraph for online deformable object tracking." In 2017 IEEE International Conference on Image Processing (ICIP). IEEE, 2017. http://dx.doi.org/10.1109/icip.2017.8296457.
Повний текст джерелаZhao, Yusheng, Xiao Luo, Wei Ju, Chong Chen, Xian-Sheng Hua, and Ming Zhang. "Dynamic Hypergraph Structure Learning for Traffic Flow Forecasting." In 2023 IEEE 39th International Conference on Data Engineering (ICDE). IEEE, 2023. http://dx.doi.org/10.1109/icde55515.2023.00178.
Повний текст джерелаSu, Lifan, Yue Gao, Xibin Zhao, Hai Wan, Ming Gu, and Jiaguang Sun. "Vertex-Weighted Hypergraph Learning for Multi-View Object Classification." In Twenty-Sixth International Joint Conference on Artificial Intelligence. California: International Joint Conferences on Artificial Intelligence Organization, 2017. http://dx.doi.org/10.24963/ijcai.2017/387.
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