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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Modeling Brain Diverse and Complex Hemodynamic Response Patterns via Deep Recurrent Autoencoder
Yan Cui, Shijie Zhao, Yaowu Chen, et al.
IEEE Transactions on Cognitive and Developmental Systems (2019) Vol. 12, Iss. 4, pp. 733-743
Open Access | Times Cited: 16

Showing 16 citing articles:

Representation learning of resting state fMRI with variational autoencoder
Jung‐Hoon Kim, Yizhen Zhang, Kuan Han, et al.
NeuroImage (2021) Vol. 241, pp. 118423-118423
Open Access | Times Cited: 42
Unveiling complex brain dynamics during movie viewing via deep recursive autoencoder model
Kexin Wang, Limei Song, Zhaowei Li, et al.
NeuroImage (2025), pp. 121177-121177
Open Access
Functional Neuroimaging in the New Era of Big Data
Xiang Li, Ning Guo, Quanzheng Li
Genomics Proteomics & Bioinformatics (2019) Vol. 17, Iss. 4, pp. 393-401
Open Access | Times Cited: 34
Long-Short-Term-Memory-Based Deep Stacked Sequence-to-Sequence Autoencoder for Health Prediction of Industrial Workers in Closed Environments Based on Wearable Devices
Weidong Xu, Jingke He, Weihua Li, et al.
Sensors (2023) Vol. 23, Iss. 18, pp. 7874-7874
Open Access | Times Cited: 10
An explainable deep learning framework for characterizing and interpreting human brain states
Shu Zhang, Junxin Wang, Sigang Yu, et al.
Medical Image Analysis (2022) Vol. 83, pp. 102665-102665
Closed Access | Times Cited: 14
Evolutional Neural Architecture Search for Optimization of Spatiotemporal Brain Network Decomposition
Qing Li, Zhang We, Lin Zhao, et al.
IEEE Transactions on Biomedical Engineering (2021) Vol. 69, Iss. 2, pp. 624-634
Closed Access | Times Cited: 17
Simultaneous spatial-temporal decomposition for connectome-scale brain networks by deep sparse recurrent auto-encoder
Qing Li, Qinglin Dong, Fangfei Ge, et al.
Brain Imaging and Behavior (2021) Vol. 15, Iss. 5, pp. 2646-2660
Closed Access | Times Cited: 15
Autoencoder and restricted Boltzmann machine for transfer learning in functional magnetic resonance imaging task classification
Jundong Hwang, Niv Lustig, Minyoung Jung, et al.
Heliyon (2023) Vol. 9, Iss. 7, pp. e18086-e18086
Open Access | Times Cited: 4
Nonlinear latent representations of high-dimensional task-fMRI data: Unveiling cognitive and behavioral insights in heterogeneous spatial maps
Mariam Zabihi, Seyed Mostafa Kia, Thomas Wolfers, et al.
PLoS ONE (2024) Vol. 19, Iss. 8, pp. e0308329-e0308329
Open Access | Times Cited: 1
Supervised Brain Network Learning Based on Deep Recurrent Neural Networks
Shijie Zhao, Yan Cui, Linwei Huang, et al.
IEEE Access (2020) Vol. 8, pp. 69967-69978
Open Access | Times Cited: 6
Identifying Individualized Functional Brain Networks: An Unsupervised Deep Temporal Attention Based Autoencoder Model
Kexin Wang, Yudan Ren, Zhengyang Liu, et al.
(2024), pp. 1-5
Closed Access
Modelling Spatio-Temporal Features of Task FMRI Data via Spatio-Temporal Fusion-Transformer
Yudan Ren, Zhenqing Ding, Ruonan Yang, et al.
(2024), pp. 1-4
Closed Access
A Compressed Sensing Network for Acquiring Human Pressure Information
Tao Han, Kuangrong Hao, Xue‐song Tang, et al.
IEEE Transactions on Cognitive and Developmental Systems (2020) Vol. 14, Iss. 2, pp. 388-402
Closed Access | Times Cited: 3
Identifying Functional Brain Networks under Naturalistic Paradigm via A Three-Dimensional Spatial Attention Convolution Autoencoder
Yudan Ren, Song Yin, Zhengyang Liu, et al.
(2024), pp. 1-4
Closed Access
Representation Learning of Resting State fMRI with Variational Autoencoder
Jung‐Hoon Kim, Yizhen Zhang, Kuan Han, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2020)
Open Access | Times Cited: 1
Heterogeneity-Aware Federated Learning for Device Anomaly Detection in Industrial loT
Zhuoer Hu, Yueming Lu, Hui Gao, et al.
2022 International Wireless Communications and Mobile Computing (IWCMC) (2022), pp. 653-659
Closed Access
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