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SympNets: Intrinsic structure-preserving symplectic networks for identifying Hamiltonian systems 期刊论文
NEURAL NETWORKS, 2020, 卷号: 132, 页码: 166-179
作者:  Jin, Pengzhan;  Zhang, Zhen;  Zhu, Aiqing;  Tang, Yifa;  Karniadakis, George Em
收藏  |  浏览/下载：143/0  |  提交时间：2021/04/26
Deep learning  Physics-informed  Dynamical systems  Hamiltonian systems  Symplectic maps  Symplectic integrators  
Circular Complex-Valued GMDH-Type Neural Network for Real-Valued Classification Problems 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2020, 卷号: 31, 期号: 12, 页码: 5285-5299
作者:  Xiao, Jin;  Jia, Yanlin;  Jiang, Xiaoyi;  Wang, Shouyang
收藏  |  浏览/下载：132/0  |  提交时间：2021/04/26
Biological system modeling  Data models  Biological neural networks  Predictive models  Neurons  Mathematical model  Complex-valued external criterion  complex-valued group method of data handling (GMDH)-type neural network  parameter estimation  real-valued classification  
Nonlinear quantum neuron: A fundamental building block for quantum neural networks 期刊论文
PHYSICAL REVIEW A, 2020, 卷号: 102, 期号: 5, 页码: 8
作者:  Yan, Shilu;  Qi, Hongsheng;  Cui, Wei
收藏  |  浏览/下载：141/0  |  提交时间：2021/01/14
Quantifying the generalization error in deep learning in terms of data distribution and neural network smoothness 期刊论文
NEURAL NETWORKS, 2020, 卷号: 130, 页码: 85-99
作者:  Jin, Pengzhan;  Lu, Lu;  Tang, Yifa;  Karniadakis, George Em
收藏  |  浏览/下载：117/0  |  提交时间：2021/01/14
Neural networks  Generalization error  Learnability  Data distribution  Cover complexity  Neural network smoothness  
Output Tracking of Boolean Control Networks 期刊论文
IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 2020, 卷号: 65, 期号: 6, 页码: 2730-2735
作者:  Zhang, Xiao;  Wang, Yuanhua;  Cheng, Daizhan
收藏  |  浏览/下载：157/0  |  提交时间：2020/09/23
Controllability  Indexes  Trajectory  Open loop systems  Artificial neural networks  Tracking loops  Control theory  Boolean control network (BCN)  control invariant subset  output tracking  semitensor product (STP)  set controllability  
Prediction of mechanical properties of micro-alloyed steels via neural networks learned by water wave optimization 期刊论文
NEURAL COMPUTING & APPLICATIONS, 2020, 卷号: 32, 期号: 10, 页码: 5583-5598
作者:  Liu, Ao;  Li, Peng;  Sun, Weiliang;  Deng, Xudong;  Li, Weigang;  Zhao, Yuntao;  Liu, Bo
收藏  |  浏览/下载：145/0  |  提交时间：2020/06/30
Neural networks  Water wave optimization  Meta-Lamarckian learning  Prediction of mechanical properties  
Rethinking Motivation of Deep Neural Architectures 期刊论文
IEEE CIRCUITS AND SYSTEMS MAGAZINE, 2020, 卷号: 20, 期号: 4, 页码: 65-76
作者:  Luo, Weilin;  Lu, Jinhu;  Li, Xuerong;  Chen, Lei;  Liu, Kexin
收藏  |  浏览/下载：136/0  |  提交时间：2021/04/26