Artículos de revistas sobre el tema "Noisy-OR model"
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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 completoJittawiriyanukoon, Chanintorn. "Estimation of regression-based model with bulk noisy data". International Journal of Electrical and Computer Engineering (IJECE) 9, n.º 5 (1 de octubre de 2019): 3649. http://dx.doi.org/10.11591/ijece.v9i5.pp3649-3656.
Texto completoHanafusa, Ryo y Takeshi Okadome. "Bayesian Kernel Regression for Noisy Inputs Based on Nadaraya–Watson Estimator Constructed from Noiseless Training Data". Advances in Data Science and Adaptive Analysis 12, n.º 01 (enero de 2020): 2050004. http://dx.doi.org/10.1142/s2424922x20500047.
Texto completoBhagawati, Rupam y Thiruselvan Subramanian. "Quantum-aided feature selection model – A quantum machine learning approach". Journal of Discrete Mathematical Sciences & Cryptography 26, n.º 3 (2023): 641–55. http://dx.doi.org/10.47974/jdmsc-1735.
Texto completoSurin, V. A. "ON PROCESSING NOISY CONTRAST IMAGES". Bulletin of the South Ural State University series "Mathematics. Mechanics. Physics" 13, n.º 1 (2021): 14–21. http://dx.doi.org/10.14529/mmph210102.
Texto completoHossain, Md Nahid, Samiul Basir, Md Shakhawat Hosen, A. O. M. Asaduzzaman, Md Mojahidul Islam, Mohammad Alamgir Hossain y Md Shohidul Islam. "Supervised Single Channel Speech Enhancement Method Using UNET". Electronics 12, n.º 14 (12 de julio de 2023): 3052. http://dx.doi.org/10.3390/electronics12143052.
Texto completoLiu, Kun-Lin, Wu-Jun Li y Minyi Guo. "Emoticon Smoothed Language Models for Twitter Sentiment Analysis". Proceedings of the AAAI Conference on Artificial Intelligence 26, n.º 1 (20 de septiembre de 2021): 1678–84. http://dx.doi.org/10.1609/aaai.v26i1.8353.
Texto completoKourehli, Seyed Sina. "Damage Assessment in Structures Using Incomplete Modal Data and Artificial Neural Network". International Journal of Structural Stability and Dynamics 15, n.º 06 (17 de junio de 2015): 1450087. http://dx.doi.org/10.1142/s0219455414500874.
Texto completoLindner, John F., Brian K. Meadows, Tracey L. Marsh, William L. Ditto y Adi R. Bulsara. "Can Neurons Distinguish Chaos from Noise?" International Journal of Bifurcation and Chaos 08, n.º 04 (abril de 1998): 767–81. http://dx.doi.org/10.1142/s0218127498000565.
Texto completoGuan, Qingji, Qinrun Chen y Yaping Huang. "An Improved Heteroscedastic Modeling Method for Chest X-ray Image Classification with Noisy Labels". Algorithms 16, n.º 5 (4 de mayo de 2023): 239. http://dx.doi.org/10.3390/a16050239.
Texto completoWei, Penghui, Wenji Mao y Guandan Chen. "A Topic-Aware Reinforced Model for Weakly Supervised Stance Detection". Proceedings of the AAAI Conference on Artificial Intelligence 33 (17 de julio de 2019): 7249–56. http://dx.doi.org/10.1609/aaai.v33i01.33017249.
Texto completoKittisuwan, Pichid. "Low-complexity image denoising based on mixture model and simple form of MMSE estimation". International Journal of Wavelets, Multiresolution and Information Processing 16, n.º 06 (10 de octubre de 2018): 1850052. http://dx.doi.org/10.1142/s0219691318500522.
Texto completoMendonça, J. Ricardo G. "The inactive–active phase transition in the noisy additive (exclusive-or) probabilistic cellular automaton". International Journal of Modern Physics C 27, n.º 02 (23 de diciembre de 2015): 1650016. http://dx.doi.org/10.1142/s0129183116500169.
Texto completoMousavi, Hamid, Mareike Buhl, Enrico Guiraud, Jakob Drefs y Jörg Lücke. "Inference and Learning in a Latent Variable Model for Beta Distributed Interval Data". Entropy 23, n.º 5 (29 de abril de 2021): 552. http://dx.doi.org/10.3390/e23050552.
Texto completoPARK, HYUNG-MIN, JONG-HWAN LEE, TAESU KIM, UN-MIN BAE, BYUNG TAEK KIM, KI-YOUNG PARK, CHANG-MIN KIM y SOO-YOUNG LEE. "MODELING AUDITORY PATHWAY FOR INTELLIGENT INFORMATION ACQUISITION". International Journal of Information Acquisition 01, n.º 04 (diciembre de 2004): 345–56. http://dx.doi.org/10.1142/s0219878904000367.
Texto completoFawwaz, Dzaky Zakiyal y Sang-Hwa Chung. "Real-Time and Robust Hydraulic System Fault Detection via Edge Computing". Applied Sciences 10, n.º 17 (27 de agosto de 2020): 5933. http://dx.doi.org/10.3390/app10175933.
Texto completoWang, Xiao Fei, Bo Nian Li, Yan Li Huang y Xin Ran Wang. "Feature Extraction from Noisy Image Using Intersecting Cortical Model". Applied Mechanics and Materials 40-41 (noviembre de 2010): 516–22. http://dx.doi.org/10.4028/www.scientific.net/amm.40-41.516.
Texto completoQin, Tianyun, Rangding Wang, Diqun Yan y Lang Lin. "Source Cell-Phone Identification in the Presence of Additive Noise from CQT Domain". Information 9, n.º 8 (17 de agosto de 2018): 205. http://dx.doi.org/10.3390/info9080205.
Texto completoLazic, Nevena, Amarnag Subramanya, Michael Ringgaard y Fernando Pereira. "Plato: A Selective Context Model for Entity Resolution". Transactions of the Association for Computational Linguistics 3 (diciembre de 2015): 503–15. http://dx.doi.org/10.1162/tacl_a_00154.
Texto completoNoh, Kyungjoo, Liang Jiang y Bill Fefferman. "Efficient classical simulation of noisy random quantum circuits in one dimension". Quantum 4 (11 de septiembre de 2020): 318. http://dx.doi.org/10.22331/q-2020-09-11-318.
Texto completoZhang, Tian Chi, Jian Pei Zhang, Jing Zhang y Melvyn L. Smith. "Two-Step Modified Nash Equilibrium Method for Medical Image Segmentation Based on an Improved C-V Model". Journal of Medical Imaging and Health Informatics 8, n.º 9 (1 de diciembre de 2018): 1826–34. http://dx.doi.org/10.1166/jmihi.2018.2521.
Texto completoMonson, Christopher K. y Kevin D. Seppi. "A Graphical Model for Evolutionary Optimization". Evolutionary Computation 16, n.º 3 (septiembre de 2008): 289–313. http://dx.doi.org/10.1162/evco.2008.16.3.289.
Texto completoYang, Lei, Haiqing Zhang, Daiwei Li, Fei Xiao y Shanglin Yang. "Facial Expression Recognition Based on Transfer Learning and SVM". Journal of Physics: Conference Series 2025, n.º 1 (1 de septiembre de 2021): 012015. http://dx.doi.org/10.1088/1742-6596/2025/1/012015.
Texto completoCedeño, Angel L., Ricardo Albornoz, Rodrigo Carvajal, Boris I. Godoy y Juan C. Agüero. "A Two-Filter Approach for State Estimation Utilizing Quantized Output Data". Sensors 21, n.º 22 (18 de noviembre de 2021): 7675. http://dx.doi.org/10.3390/s21227675.
Texto completoPeeters, Bert y Ard Kuijpers. "Classification of noisy vehicles from unsupervised measurements". INTER-NOISE and NOISE-CON Congress and Conference Proceedings 265, n.º 5 (1 de febrero de 2023): 2175–84. http://dx.doi.org/10.3397/in_2022_0312.
Texto completoAbdel Qader, Akram. "A New Novel Hybrid Dynamic Color Segmentation Model for Road Signs in Noisy Conditions". International Journal of Software Innovation 9, n.º 3 (julio de 2021): 1–22. http://dx.doi.org/10.4018/ijsi.2021070101.
Texto completoRymarczyk, Tomasz, Krzysztof Polakowski y Jan Sikora. "A NEW CONCEPT OF DISCRETIZATION MODEL FOR IMAGING IMPROVING IN ULTRASOUND TRANSMISSION TOMOGRAPHY". Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska 9, n.º 4 (15 de diciembre de 2019): 48–51. http://dx.doi.org/10.35784/iapgos.131.
Texto completoJi, S. y X. Yuan. "A GENERIC PROBABILISTIC MODEL AND A HIERARCHICAL SOLUTION FOR SENSOR LOCALIZATION IN NOISY AND RESTRICTED CONDITIONS". ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B1 (3 de junio de 2016): 193–98. http://dx.doi.org/10.5194/isprsarchives-xli-b1-193-2016.
Texto completoJi, S. y X. Yuan. "A GENERIC PROBABILISTIC MODEL AND A HIERARCHICAL SOLUTION FOR SENSOR LOCALIZATION IN NOISY AND RESTRICTED CONDITIONS". ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B1 (3 de junio de 2016): 193–98. http://dx.doi.org/10.5194/isprs-archives-xli-b1-193-2016.
Texto completoMayhew, Stephen, Gupta Nitish y Dan Roth. "Robust Named Entity Recognition with Truecasing Pretraining". Proceedings of the AAAI Conference on Artificial Intelligence 34, n.º 05 (3 de abril de 2020): 8480–87. http://dx.doi.org/10.1609/aaai.v34i05.6368.
Texto completoZhang, Jun, Wen Yao, Xiaoqian Chen y Ling Feng. "Transferable Post-hoc Calibration on Pretrained Transformers in Noisy Text Classification". Proceedings of the AAAI Conference on Artificial Intelligence 37, n.º 11 (26 de junio de 2023): 13940–48. http://dx.doi.org/10.1609/aaai.v37i11.26632.
Texto completoBocquet, Marc, Julien Brajard, Alberto Carrassi y Laurent Bertino. "Data assimilation as a learning tool to infer ordinary differential equation representations of dynamical models". Nonlinear Processes in Geophysics 26, n.º 3 (10 de julio de 2019): 143–62. http://dx.doi.org/10.5194/npg-26-143-2019.
Texto completoZhang, Rui, Zhenghao Chen, Sanxing Zhang, Fei Song, Gang Zhang, Quancheng Zhou y Tao Lei. "Remote Sensing Image Scene Classification with Noisy Label Distillation". Remote Sensing 12, n.º 15 (24 de julio de 2020): 2376. http://dx.doi.org/10.3390/rs12152376.
Texto completoTang, Ning, Zi-Long Fan y Hao-Sheng Zeng. "Improving the quality of noisy spatial quantum channels". Quantum Information and Computation 15, n.º 7&8 (mayo de 2015): 568–81. http://dx.doi.org/10.26421/qic15.7-8-3.
Texto completoRohling, Jos H. T. y Janusz M. Meylahn. "Two-Community Noisy Kuramoto Model Suggests Mechanism for Splitting in the Suprachiasmatic Nucleus". Journal of Biological Rhythms 35, n.º 2 (23 de enero de 2020): 158–66. http://dx.doi.org/10.1177/0748730419898314.
Texto completoKlawonn, Matthew, Eric Heim y James Hendler. "Exploiting Class Learnability in Noisy Data". Proceedings of the AAAI Conference on Artificial Intelligence 33 (17 de julio de 2019): 4082–89. http://dx.doi.org/10.1609/aaai.v33i01.33014082.
Texto completoGuo, Zhenyu, Yujuan Sun, Muwei Jian y Xiaofeng Zhang. "Deep Residual Network with Sparse Feedback for Image Restoration". Applied Sciences 8, n.º 12 (28 de noviembre de 2018): 2417. http://dx.doi.org/10.3390/app8122417.
Texto completoNorthcutt, Curtis, Lu Jiang y Isaac Chuang. "Confident Learning: Estimating Uncertainty in Dataset Labels". Journal of Artificial Intelligence Research 70 (14 de abril de 2021): 1373–411. http://dx.doi.org/10.1613/jair.1.12125.
Texto completoWu, Biao, Yong Huang, Xiang Chen, Sridhar Krishnaswamy y Hui Li. "Guided-wave signal processing by the sparse Bayesian learning approach employing Gabor pulse model". Structural Health Monitoring 16, n.º 3 (29 de agosto de 2016): 347–62. http://dx.doi.org/10.1177/1475921716665252.
Texto completoKaur, Inderjit y Dr Pardeep Saini. "Classifier Model using Artificial Neural Network". International Journal of Engineering, Business and Management 7, n.º 4 (2023): 69–73. http://dx.doi.org/10.22161/ijebm.7.4.11.
Texto completoStark, Oliver, Martin Pfeifer y Sören Hohmann. "Parameter and Order Identification of Fractional Systems with Application to a Lithium-Ion Battery". Mathematics 9, n.º 14 (8 de julio de 2021): 1607. http://dx.doi.org/10.3390/math9141607.
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