Adaptive temporal-difference learning via deep neural network function approximation: a non-asymptotic analysis by Guoyong Wang, Tiange Fu, Ruijuan Zheng, Xuhui Zhao, Junlong Zhu, Mingchuan Zhang

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Brain network for small-scale features in active touch by Saeed Babadi, Roger Gassert, Vincent Hayward, Marco Piccirelli, Spyros Kollias, Theodore E. Milner

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The Comparison of Activation Functions in Feature Extraction Layer using Sharpen Filter by Oktavia Citra Resmi Rachmawati, Ali Ridho Barakbah, Tita Karlita

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Optimal feedback control of dynamical systems via value-function approximation by Kunisch, Karl, Walter, Daniel

“…It relies on parameter dependent approximations to the optimal value function obtained from a family of universal approximators. …”
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Hubs, influencers, and communities of executive functions: a task-based fMRI graph analysis by Alexandra T. Davis

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Hypoxia’s Impact on Hippocampal Functional Connectivity: Insights from Resting-State fMRI Studies by Julia Micaux, Abir Troudi Habibi, Franck Mauconduit, Marion Noulhiane

Subjects: “…resting-state functional MRI…”
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Vagus nerve stimulation balanced disrupted default-mode network and salience network in a postsurgical epileptic patient by Wang KL, Chai Q, Qiao H, Zhang JG, Liu TH, Meng FG

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Load-Balanced Dynamic SFC Migration Based on Resource Demand Prediction by Tian Sun, Hefei Hu, Sirui Zhang

Subjects: “…network function virtualization…”
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Optimizing Activation Function for Parameter Reduction in CNNs on CIFAR-10 and CINIC-10 by Vasil Vasilev, Vasil Shterev, Maria Nenova

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A deeper exploration of functional connectivity of brain regions regulating bladder function in healthy adults by Arda Bayer, Kris Hoffman, Betsy Salazar, Behnaam Aazhang, Rose Khavari

“…This study analyzes the changes in the resting state functional connectivity (rsFC) network involving regions of the brain, brainstem, and cerebellum in healthy adults with respect to conventional pairwise rsFC and four rsFC global network statistics. …”
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SUPERMAGOv2: Protein Function Prediction via Transformer Embeddings and Bitscore-Weighted Features by Gabriel Bianchin de Oliveira, Helio Pedrini, Zanoni Dias

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Neuroimaging Changes in the Sensorimotor Network and Visual Network in Bipolar Disorder and Their Relationship with Genetic Characteristics by Chunguo Zhang, Yiding Han, Haohao Yan, Yangpan Ou, Jiaquan Liang, Wei Huang, Xiaoling Li, Chaohua Tang, Jinbing Xu, Guojun Xie, Wenbin Guo

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Small-World Propensity Reveals the Frequency Specificity of Resting State Networks by Riccardo Iandolo, Marianna Semprini, Stefano Buccelli, Federico Barban, Mingqi Zhao, Jessica Samogin, Gaia Bonassi, Laura Avanzino, Dante Mantini, Michela Chiappalone

“…<italic>Goal:</italic> Functional connectivity (FC) is an important indicator of the brain&#x0027;s state in different conditions, such as rest&#x002F;task or health&#x002F;pathology. …”
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Editorial: New applications of biological and computational neural networks in brain imaging by Prasanna Parvathaneni

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Cross-Dataset Head-Related Transfer Function Harmonization Based on Perceptually Relevant Loss Function by Jiale Zhao, Dingding Yao, Junfeng Li

“…Head-Related Transfer Functions (HRTFs) play a vital role in binaural spatial audio rendering. …”
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Brain functional connectivity characteristics at various levels of inhibitory function in elderly individuals with cognitive impairment by Xin Xin, Zixian Wang, Shuqi Jia, Shufan Li, Qing Liu, Xingze Wang, Xing Wang

“…Abstract This study aims to explore the brain network connectivity patterns in elderly individuals with cognitive impairment at varying levels of inhibitory function and to identify key brain connectivity features that influence inhibitory function. …”
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Enhanced force field construction for graphene monolayers via neural network-based fitting of density functional theory data by Phạm Tấn Tiến, Trần Bảo Tiến, Bùi Quốc Việt

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STATISTICAL SIMULATION OF RELIABILITY OF NETWORKS WITH EXPONENTIALLY DISTRIBUTED UNIT LIFETIMES by ROTARU, Maria

“…It was shown that the most important theoretical characteristics of lifetime for such networks, as the mean value, the variance, the survival/reliability function, my be approximated, with desired accuracy, by the same corresponding characteristics, as the sample mean value, sample variance, empirical survival/reliability function simulated by Monte-Carlo methods. …”
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Research on network traffic prediction based on Bi-GRU model by Xu Haibing, Guo Jiuming

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Improving deep convolutional neural networks with mixed maxout units by Hui-zhen ZHAO, Fu-xian LIU, Long-yue LI, Chang LUO

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