Literatura académica sobre el tema "Noisy-OR model"
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Artículos de revistas sobre el tema "Noisy-OR model"
Quintanar-Gago, David A. y Pamela F. Nelson. "The extended Recursive Noisy OR model: Static and dynamic considerations". International Journal of Approximate Reasoning 139 (diciembre de 2021): 185–200. http://dx.doi.org/10.1016/j.ijar.2021.09.013.
Texto completoZhou, Kuang, Arnaud Martin y Quan Pan. "The Belief Noisy-OR Model Applied to Network Reliability Analysis". International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 24, n.º 06 (30 de noviembre de 2016): 937–60. http://dx.doi.org/10.1142/s0218488516500434.
Texto completoLi, W., P. Poupart y P. Van Beek. "Exploiting Structure in Weighted Model Counting Approaches to Probabilistic Inference". Journal of Artificial Intelligence Research 40 (19 de abril de 2011): 729–65. http://dx.doi.org/10.1613/jair.3232.
Texto completoBüttner, Martha, Lisa Schneider, Aleksander Krasowski, Joachim Krois, Ben Feldberg y Falk Schwendicke. "Impact of Noisy Labels on Dental Deep Learning—Calculus Detection on Bitewing Radiographs". Journal of Clinical Medicine 12, n.º 9 (23 de abril de 2023): 3058. http://dx.doi.org/10.3390/jcm12093058.
Texto completoShang, Yuming, He-Yan Huang, Xian-Ling Mao, Xin Sun y Wei Wei. "Are Noisy Sentences Useless for Distant Supervised Relation Extraction?" Proceedings of the AAAI Conference on Artificial Intelligence 34, n.º 05 (3 de abril de 2020): 8799–806. http://dx.doi.org/10.1609/aaai.v34i05.6407.
Texto completoZheng, Guoqing, Ahmed Hassan Awadallah y Susan Dumais. "Meta Label Correction for Noisy Label Learning". Proceedings of the AAAI Conference on Artificial Intelligence 35, n.º 12 (18 de mayo de 2021): 11053–61. http://dx.doi.org/10.1609/aaai.v35i12.17319.
Texto completoMaeda, Shin-ichi, Wen-Jie Song y Shin Ishii. "Nonlinear and Noisy Extension of Independent Component Analysis: Theory and Its Application to a Pitch Sensation Model". Neural Computation 17, n.º 1 (1 de enero de 2005): 115–44. http://dx.doi.org/10.1162/0899766052530866.
Texto completoZhan, Peida, Hong Jiao, Kaiwen Man y Lijun Wang. "Using JAGS for Bayesian Cognitive Diagnosis Modeling: A Tutorial". Journal of Educational and Behavioral Statistics 44, n.º 4 (10 de febrero de 2019): 473–503. http://dx.doi.org/10.3102/1076998619826040.
Texto completoHong, Zhiwei, Xiaocheng Fan, Tao Jiang y Jianxing Feng. "End-to-End Unpaired Image Denoising with Conditional Adversarial Networks". Proceedings of the AAAI Conference on Artificial Intelligence 34, n.º 04 (3 de abril de 2020): 4140–49. http://dx.doi.org/10.1609/aaai.v34i04.5834.
Texto completoKağan Akkaya, Emre y Burcu Can. "Transfer learning for Turkish named entity recognition on noisy text". Natural Language Engineering 27, n.º 1 (28 de enero de 2020): 35–64. http://dx.doi.org/10.1017/s1351324919000627.
Texto completoTesis sobre el tema "Noisy-OR model"
Li, Wei. "Exploiting Structure in Backtracking Algorithms for Propositional and Probabilistic Reasoning". Thesis, 2010. http://hdl.handle.net/10012/5322.
Texto completoLibros sobre el tema "Noisy-OR model"
Back, Kerry E. Rational Expectations Equilibria. Oxford University Press, 2017. http://dx.doi.org/10.1093/acprof:oso/9780190241148.003.0022.
Texto completoPortillo, Rafael, Filiz Unsal, Stephen O’Connell y Catherine Pattillo. Implementation Errors and Incomplete Information. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198785811.003.0009.
Texto completoGolan, Amos. Foundations of Info-Metrics. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780199349524.001.0001.
Texto completoCapítulos de libros sobre el tema "Noisy-OR model"
Woudenberg, Steven P. D. y Linda C. van der Gaag. "Using the Noisy-OR Model Can Be Harmful … But It Often Is Not". En Lecture Notes in Computer Science, 122–33. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-22152-1_11.
Texto completoBolt, Janneke H. y Linda C. van der Gaag. "An Empirical Study of the Use of the Noisy-Or Model in a Real-Life Bayesian Network". En Communications in Computer and Information Science, 11–20. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-14055-6_2.
Texto completoGuan, Ji, Wang Fang y Mingsheng Ying. "Verifying Fairness in Quantum Machine Learning". En Computer Aided Verification, 408–29. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-13188-2_20.
Texto completoCohen, Albert, Wolfgang Dahmen y Ron DeVore. "State Estimation—The Role of Reduced Models". En SEMA SIMAI Springer Series, 57–77. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-86236-7_4.
Texto completoSalotti, Jean Marc. "Noisy-or Nodes for Conditioning Models". En From Animals to Animats 11, 458–67. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-15193-4_43.
Texto completoWalrand, Jean. "Speech Recognition: A". En Probability in Electrical Engineering and Computer Science, 205–15. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-49995-2_11.
Texto completoKoltai, Júlia, Zoltán Kmetty y Károly Bozsonyi. "From Durkheim to Machine Learning: Finding the Relevant Sociological Content in Depression and Suicide-Related Social Media Discourses". En Pathways Between Social Science and Computational Social Science, 237–58. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-54936-7_11.
Texto completoSrinivas, Sampath. "A Generalization of the Noisy-Or Model". En Uncertainty in Artificial Intelligence, 208–15. Elsevier, 1993. http://dx.doi.org/10.1016/b978-1-4832-1451-1.50030-5.
Texto completoBusemeyer, Marius R. y Julian L. Garritzmann. "Loud, Noisy, or Quiet Politics?" En The World Politics of Social Investment: Volume II, 59–85. Oxford University Press, 2022. http://dx.doi.org/10.1093/oso/9780197601457.003.0003.
Texto completoRodgers, Waymond. "The Expedient Algorithmic Pathway". En Dominant Algorithms to Evaluate Artificial Intelligence: From the view of Throughput Model, 96–129. BENTHAM SCIENCE PUBLISHERS, 2022. http://dx.doi.org/10.2174/9789815049541122010006.
Texto completoActas de conferencias sobre el tema "Noisy-OR model"
Nagesh, Ajay, Gholamreza Haffari y Ganesh Ramakrishnan. "Noisy Or-based model for Relation Extraction using Distant Supervision". En Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP). Stroudsburg, PA, USA: Association for Computational Linguistics, 2014. http://dx.doi.org/10.3115/v1/d14-1208.
Texto completoRamakrishnan, Ganesh, Krishna Prasad Chitrapura, Raghu Krishnapuram y Pushpak Bhattacharyya. "A model for handling approximate, noisy or incomplete labeling in text classification". En the 22nd international conference. New York, New York, USA: ACM Press, 2005. http://dx.doi.org/10.1145/1102351.1102437.
Texto completoYongjian Hu, Yunfei Zhou, Xuefei Jiang, Zhihuai Xiao y Zhaohui Sun. "Study of Hydropower Units Fault Diagnosis based on Bayesian Network Noisy Or Model". En 2014 ISFMFE - 6th International Symposium on Fluid Machinery and Fluid Engineering. Institution of Engineering and Technology, 2014. http://dx.doi.org/10.1049/cp.2014.1132.
Texto completoLi, Zhaohui, Xiaogang Wang, Wan Qiu y Dongxin Shi. "Research on Intelligent Traditional Chinese Medicine Prescription Model Based on Noisy-or Bayesian Network". En 2020 International Conference on Culture-oriented Science & Technology (ICCST). IEEE, 2020. http://dx.doi.org/10.1109/iccst50977.2020.00100.
Texto completoPan, Weiran, Wei Wei y Feida Zhu. "Automatic Noisy Label Correction for Fine-Grained Entity Typing". En 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.2022/599.
Texto completoPark, Jun H. y N. Sri Namachchivaya. "Noisy Impact Oscillators". En ASME 2004 International Mechanical Engineering Congress and Exposition. ASMEDC, 2004. http://dx.doi.org/10.1115/imece2004-60861.
Texto completoAsl, Sajjad Fekri, Michael Athans y Antonio Pascoal. "Estimation and Identification of Mass-Spring-Dashpot Systems Using Multiple-Model Adaptive Algorithms". En ASME 2002 International Mechanical Engineering Congress and Exposition. ASMEDC, 2002. http://dx.doi.org/10.1115/imece2002-33442.
Texto completoWu, Junshuang, Richong Zhang, Yongyi Mao, Hongyu Guo y Jinpeng Huai. "Modeling Noisy Hierarchical Types in Fine-Grained Entity Typing: A Content-Based Weighting Approach". En 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.2019/731.
Texto completoWong, Harry W. H., Jack P. K. Ma, Donald P. H. Wong, Lucien K. L. Ng y Sherman S. M. Chow. "Learning Model with Error -- Exposing the Hidden Model of BAYHENN". En Twenty-Ninth International Joint Conference on Artificial Intelligence and Seventeenth Pacific Rim International Conference on Artificial Intelligence {IJCAI-PRICAI-20}. California: International Joint Conferences on Artificial Intelligence Organization, 2020. http://dx.doi.org/10.24963/ijcai.2020/488.
Texto completoChoi, Seunggil y N. Sri Namachchivaya. "An Averaging Approach for Noisy Strongly Nonlinear Periodically Forced Systems". En ASME 2002 International Mechanical Engineering Congress and Exposition. ASMEDC, 2002. http://dx.doi.org/10.1115/imece2002-39384.
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