Статті в журналах з теми "Lipschitz neural network"
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Zhu, Zelong, Chunna Zhao, and Yaqun Huang. "Fractional order Lipschitz recurrent neural network with attention for long time series prediction." Journal of Physics: Conference Series 2813, no. 1 (August 1, 2024): 012015. http://dx.doi.org/10.1088/1742-6596/2813/1/012015.
Повний текст джерелаZhang, Huan, Pengchuan Zhang, and Cho-Jui Hsieh. "RecurJac: An Efficient Recursive Algorithm for Bounding Jacobian Matrix of Neural Networks and Its Applications." Proceedings of the AAAI Conference on Artificial Intelligence 33 (July 17, 2019): 5757–64. http://dx.doi.org/10.1609/aaai.v33i01.33015757.
Повний текст джерелаAraujo, Alexandre, Benjamin Negrevergne, Yann Chevaleyre, and Jamal Atif. "On Lipschitz Regularization of Convolutional Layers using Toeplitz Matrix Theory." Proceedings of the AAAI Conference on Artificial Intelligence 35, no. 8 (May 18, 2021): 6661–69. http://dx.doi.org/10.1609/aaai.v35i8.16824.
Повний текст джерелаXu, Yuhui, Wenrui Dai, Yingyong Qi, Junni Zou, and Hongkai Xiong. "Iterative Deep Neural Network Quantization With Lipschitz Constraint." IEEE Transactions on Multimedia 22, no. 7 (July 2020): 1874–88. http://dx.doi.org/10.1109/tmm.2019.2949857.
Повний текст джерелаMohammad, Ibtihal J. "Neural Networks of the Rational r-th Powers of the Multivariate Bernstein Operators." BASRA JOURNAL OF SCIENCE 40, no. 2 (September 1, 2022): 258–73. http://dx.doi.org/10.29072/basjs.20220201.
Повний текст джерелаIbtihal.J.M and Ali J. Mohammad. "Neural Network of Multivariate Square Rational Bernstein Operators with Positive Integer Parameter." European Journal of Pure and Applied Mathematics 15, no. 3 (July 31, 2022): 1189–200. http://dx.doi.org/10.29020/nybg.ejpam.v15i3.4425.
Повний текст джерелаLiu, Kanglin, and Guoping Qiu. "Lipschitz constrained GANs via boundedness and continuity." Neural Computing and Applications 32, no. 24 (May 24, 2020): 18271–83. http://dx.doi.org/10.1007/s00521-020-04954-z.
Повний текст джерелаOthmani, S., N. E. Tatar, and A. Khemmoudj. "Asymptotic behavior of a BAM neural network with delays of distributed type." Mathematical Modelling of Natural Phenomena 16 (2021): 29. http://dx.doi.org/10.1051/mmnp/2021023.
Повний текст джерелаXia, Youshen. "An Extended Projection Neural Network for Constrained Optimization." Neural Computation 16, no. 4 (April 1, 2004): 863–83. http://dx.doi.org/10.1162/089976604322860730.
Повний текст джерелаLi, Peiluan, Yuejing Lu, Changjin Xu, and Jing Ren. "Bifurcation Phenomenon and Control Technique in Fractional BAM Neural Network Models Concerning Delays." Fractal and Fractional 7, no. 1 (December 22, 2022): 7. http://dx.doi.org/10.3390/fractalfract7010007.
Повний текст джерелаWei Bian and Xiaojun Chen. "Smoothing Neural Network for Constrained Non-Lipschitz Optimization With Applications." IEEE Transactions on Neural Networks and Learning Systems 23, no. 3 (March 2012): 399–411. http://dx.doi.org/10.1109/tnnls.2011.2181867.
Повний текст джерелаChen, Xin, Yujuan Si, Zhanyuan Zhang, Wenke Yang, and Jianchao Feng. "Improving Adversarial Robustness of ECG Classification Based on Lipschitz Constraints and Channel Activation Suppression." Sensors 24, no. 9 (May 6, 2024): 2954. http://dx.doi.org/10.3390/s24092954.
Повний текст джерелаZhang, Chi, Wenjie Ruan, and Peipei Xu. "Reachability Analysis of Neural Network Control Systems." Proceedings of the AAAI Conference on Artificial Intelligence 37, no. 12 (June 26, 2023): 15287–95. http://dx.doi.org/10.1609/aaai.v37i12.26783.
Повний текст джерелаYu, Hongshan, Jinzhu Peng, and Yandong Tang. "Identification of Nonlinear Dynamic Systems Using Hammerstein-Type Neural Network." Mathematical Problems in Engineering 2014 (2014): 1–9. http://dx.doi.org/10.1155/2014/959507.
Повний текст джерелаXin, YU, WU Lingzhen, XIE Mian, WANG Yanlin, XU Liuming, LU Huixia, and XU Chenhua. "Smoothing Neural Network for Non‐Lipschitz Optimization with Linear Inequality Constraints." Chinese Journal of Electronics 30, no. 4 (July 2021): 634–43. http://dx.doi.org/10.1049/cje.2021.05.005.
Повний текст джерелаZhao, Chunna, Junjie Ye, Zelong Zhu, and Yaqun Huang. "FLRNN-FGA: Fractional-Order Lipschitz Recurrent Neural Network with Frequency-Domain Gated Attention Mechanism for Time Series Forecasting." Fractal and Fractional 8, no. 7 (July 22, 2024): 433. http://dx.doi.org/10.3390/fractalfract8070433.
Повний текст джерелаLiang, Youwei, and Dong Huang. "Large Norms of CNN Layers Do Not Hurt Adversarial Robustness." Proceedings of the AAAI Conference on Artificial Intelligence 35, no. 10 (May 18, 2021): 8565–73. http://dx.doi.org/10.1609/aaai.v35i10.17039.
Повний текст джерелаZhuo, Li’an, Baochang Zhang, Chen Chen, Qixiang Ye, Jianzhuang Liu, and David Doermann. "Calibrated Stochastic Gradient Descent for Convolutional Neural Networks." Proceedings of the AAAI Conference on Artificial Intelligence 33 (July 17, 2019): 9348–55. http://dx.doi.org/10.1609/aaai.v33i01.33019348.
Повний текст джерелаLippl, Samuel, Benjamin Peters, and Nikolaus Kriegeskorte. "Can neural networks benefit from objectives that encourage iterative convergent computations? A case study of ResNets and object classification." PLOS ONE 19, no. 3 (March 21, 2024): e0293440. http://dx.doi.org/10.1371/journal.pone.0293440.
Повний текст джерелаFeyzdar, Mahdi, Ahmad Reza Vali та Valiollah Babaeipour. "Identification and Optimization of Recombinant E. coli Fed-Batch Fermentation Producing γ-Interferon Protein". International Journal of Chemical Reactor Engineering 11, № 1 (18 червня 2013): 123–34. http://dx.doi.org/10.1515/ijcre-2012-0081.
Повний текст джерелаStamova, Ivanka, Trayan Stamov, and Gani Stamov. "Lipschitz stability analysis of fractional-order impulsive delayed reaction-diffusion neural network models." Chaos, Solitons & Fractals 162 (September 2022): 112474. http://dx.doi.org/10.1016/j.chaos.2022.112474.
Повний текст джерелаChen, Yu-Wen, Ming-Li Chiang, and Li-Chen Fu. "Adaptive Formation Control for Multiple Quadrotors with Nonlinear Uncertainties Using Lipschitz Neural Network." IFAC-PapersOnLine 56, no. 2 (2023): 8714–19. http://dx.doi.org/10.1016/j.ifacol.2023.10.053.
Повний текст джерелаLi, Wenjing, Wei Bian, and Xiaoping Xue. "Projected Neural Network for a Class of Non-Lipschitz Optimization Problems With Linear Constraints." IEEE Transactions on Neural Networks and Learning Systems 31, no. 9 (September 2020): 3361–73. http://dx.doi.org/10.1109/tnnls.2019.2944388.
Повний текст джерелаAkrour, Riad, Asma Atamna, and Jan Peters. "Convex optimization with an interpolation-based projection and its application to deep learning." Machine Learning 110, no. 8 (July 19, 2021): 2267–89. http://dx.doi.org/10.1007/s10994-021-06037-z.
Повний текст джерелаHumphries, Usa, Grienggrai Rajchakit, Pramet Kaewmesri, Pharunyou Chanthorn, Ramalingam Sriraman, Rajendran Samidurai, and Chee Peng Lim. "Global Stability Analysis of Fractional-Order Quaternion-Valued Bidirectional Associative Memory Neural Networks." Mathematics 8, no. 5 (May 14, 2020): 801. http://dx.doi.org/10.3390/math8050801.
Повний текст джерелаBensidhoum, Tarek, Farah Bouakrif, and Michel Zasadzinski. "Iterative learning radial basis function neural networks control for unknown multi input multi output nonlinear systems with unknown control direction." Transactions of the Institute of Measurement and Control 41, no. 12 (February 19, 2019): 3452–67. http://dx.doi.org/10.1177/0142331219826659.
Повний текст джерелаZhang, Fan, Heng-You Lan, and Hai-Yang Xu. "Generalized Hukuhara Weak Solutions for a Class of Coupled Systems of Fuzzy Fractional Order Partial Differential Equations without Lipschitz Conditions." Mathematics 10, no. 21 (October 30, 2022): 4033. http://dx.doi.org/10.3390/math10214033.
Повний текст джерелаLaurel, Jacob, Rem Yang, Shubham Ugare, Robert Nagel, Gagandeep Singh, and Sasa Misailovic. "A general construction for abstract interpretation of higher-order automatic differentiation." Proceedings of the ACM on Programming Languages 6, OOPSLA2 (October 31, 2022): 1007–35. http://dx.doi.org/10.1145/3563324.
Повний текст джерелаTatar, Nasser-Eddine. "Long Time Behavior for a System of Differential Equations with Non-Lipschitzian Nonlinearities." Advances in Artificial Neural Systems 2014 (September 14, 2014): 1–7. http://dx.doi.org/10.1155/2014/252674.
Повний текст джерелаLi, Jia, Cong Fang, and Zhouchen Lin. "Lifted Proximal Operator Machines." Proceedings of the AAAI Conference on Artificial Intelligence 33 (July 17, 2019): 4181–88. http://dx.doi.org/10.1609/aaai.v33i01.33014181.
Повний текст джерелаCantarini, Marco, Lucian Coroianu, Danilo Costarelli, Sorin G. Gal, and Gianluca Vinti. "Inverse Result of Approximation for the Max-Product Neural Network Operators of the Kantorovich Type and Their Saturation Order." Mathematics 10, no. 1 (December 25, 2021): 63. http://dx.doi.org/10.3390/math10010063.
Повний текст джерелаZhao, Liquan, and Yan Liu. "Spectral Normalization for Domain Adaptation." Information 11, no. 2 (January 27, 2020): 68. http://dx.doi.org/10.3390/info11020068.
Повний текст джерелаPantoja-Garcia, Luis, Vicente Parra-Vega, Rodolfo Garcia-Rodriguez, and Carlos Ernesto Vázquez-García. "A Novel Actor—Critic Motor Reinforcement Learning for Continuum Soft Robots." Robotics 12, no. 5 (October 9, 2023): 141. http://dx.doi.org/10.3390/robotics12050141.
Повний текст джерелаVan, Mien. "Higher-order terminal sliding mode controller for fault accommodation of Lipschitz second-order nonlinear systems using fuzzy neural network." Applied Soft Computing 104 (June 2021): 107186. http://dx.doi.org/10.1016/j.asoc.2021.107186.
Повний текст джерелаJiao, Yulin, Feng Xiao, Wenjuan Zhang, Shujuan Huang, Hao Lu, and Zhaoting Lu. "Image Inpainting based on Gated Convolution and spectral Normalization." Frontiers in Computing and Intelligent Systems 6, no. 2 (December 5, 2023): 96–100. http://dx.doi.org/10.54097/wkezn917.
Повний текст джерелаLi, Cuiying, Rui Wu, and Ranzhuo Ma. "Existence of solutions for Caputo fractional iterative equations under several boundary value conditions." AIMS Mathematics 8, no. 1 (2022): 317–39. http://dx.doi.org/10.3934/math.2023015.
Повний текст джерелаTong, Qingbin, Feiyu Lu, Ziwei Feng, Qingzhu Wan, Guoping An, Junci Cao, and Tao Guo. "A Novel Method for Fault Diagnosis of Bearings with Small and Imbalanced Data Based on Generative Adversarial Networks." Applied Sciences 12, no. 14 (July 21, 2022): 7346. http://dx.doi.org/10.3390/app12147346.
Повний текст джерелаPauli, Patricia, Anne Koch, Julian Berberich, Paul Kohler, and Frank Allgower. "Training Robust Neural Networks Using Lipschitz Bounds." IEEE Control Systems Letters 6 (2022): 121–26. http://dx.doi.org/10.1109/lcsys.2021.3050444.
Повний текст джерелаNegrini, Elisa, Giovanna Citti, and Luca Capogna. "System identification through Lipschitz regularized deep neural networks." Journal of Computational Physics 444 (November 2021): 110549. http://dx.doi.org/10.1016/j.jcp.2021.110549.
Повний текст джерелаZou, Dongmian, Radu Balan, and Maneesh Singh. "On Lipschitz Bounds of General Convolutional Neural Networks." IEEE Transactions on Information Theory 66, no. 3 (March 2020): 1738–59. http://dx.doi.org/10.1109/tit.2019.2961812.
Повний текст джерелаLaurel, Jacob, Rem Yang, Gagandeep Singh, and Sasa Misailovic. "A dual number abstraction for static analysis of Clarke Jacobians." Proceedings of the ACM on Programming Languages 6, POPL (January 16, 2022): 1–30. http://dx.doi.org/10.1145/3498718.
Повний текст джерелаGarcía Cabello, Julia. "Mathematical Neural Networks." Axioms 11, no. 2 (February 17, 2022): 80. http://dx.doi.org/10.3390/axioms11020080.
Повний текст джерелаMa, Shuo, and Yanmei Kang. "Exponential synchronization of delayed neutral-type neural networks with Lévy noise under non-Lipschitz condition." Communications in Nonlinear Science and Numerical Simulation 57 (April 2018): 372–87. http://dx.doi.org/10.1016/j.cnsns.2017.10.012.
Повний текст джерелаNeumayer, Sebastian, Alexis Goujon, Pakshal Bohra, and Michael Unser. "Approximation of Lipschitz Functions Using Deep Spline Neural Networks." SIAM Journal on Mathematics of Data Science 5, no. 2 (May 15, 2023): 306–22. http://dx.doi.org/10.1137/22m1504573.
Повний текст джерелаSong, Xueli, and Jigen Peng. "Global Asymptotic Stability of Impulsive CNNs with Proportional Delays and Partially Lipschitz Activation Functions." Abstract and Applied Analysis 2014 (2014): 1–11. http://dx.doi.org/10.1155/2014/832892.
Повний текст джерелаHan, Fangfang, Bin Liu, Junchao Zhu, and Baofeng Zhang. "Algorithm Design for Edge Detection of High-Speed Moving Target Image under Noisy Environment." Sensors 19, no. 2 (January 16, 2019): 343. http://dx.doi.org/10.3390/s19020343.
Повний текст джерелаBecktor, Jonathan, Frederik Schöller, Evangelos Boukas, Mogens Blanke, and Lazaros Nalpantidis. "Lipschitz Constrained Neural Networks for Robust Object Detection at Sea." IOP Conference Series: Materials Science and Engineering 929 (November 27, 2020): 012023. http://dx.doi.org/10.1088/1757-899x/929/1/012023.
Повний текст джерелаAziznejad, Shayan, Harshit Gupta, Joaquim Campos, and Michael Unser. "Deep Neural Networks With Trainable Activations and Controlled Lipschitz Constant." IEEE Transactions on Signal Processing 68 (2020): 4688–99. http://dx.doi.org/10.1109/tsp.2020.3014611.
Повний текст джерелаDelaney, Blaise, Nicole Schulte, Gregory Ciezarek, Niklas Nolte, Mike Williams, and Johannes Albrecht. "Applications of Lipschitz neural networks to the Run 3 LHCb trigger system." EPJ Web of Conferences 295 (2024): 09005. http://dx.doi.org/10.1051/epjconf/202429509005.
Повний текст джерелаMallat, Stéphane, Sixin Zhang, and Gaspar Rochette. "Phase harmonic correlations and convolutional neural networks." Information and Inference: A Journal of the IMA 9, no. 3 (November 5, 2019): 721–47. http://dx.doi.org/10.1093/imaiai/iaz019.
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