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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:

Deep Learning for Time Series Forecasting: Tutorial and Literature Survey
Konstantinos Benidis, Syama Sundar Rangapuram, Valentín Flunkert, et al.
ACM Computing Surveys (2022) Vol. 55, Iss. 6, pp. 1-36
Open Access | Times Cited: 124

Showing 26-50 of 124 citing articles:

Informer in Algorithmic Investment Strategies on High Frequency Bitcoin Data
Filip Stefaniuk, Robert Ślepaczuk
(2025)
Closed Access
Predictive Recurrent Neural Networks Based Carbon Price Forecasting: A Generative Perspective
Zhong Zheng, Yan Zhang
Computational Economics (2025)
Closed Access
Unveiling Time Series Patterns: A Deep Learning Approach for Accurate Forecasting
Prabhdeep Singh, Kiran Deep Singh, G. L. Saini
Smart innovation, systems and technologies (2025), pp. 431-440
Closed Access
Spatio-Temporal NDVI Prediction for Rice Crop
Anamika Dey, Somrita Sarkar, Arijit Mondal, et al.
SN Computer Science (2025) Vol. 6, Iss. 3
Closed Access
Time-series forecasting in smart manufacturing systems: An experimental evaluation of the state-of-the-art algorithms
Mojtaba A. Farahani, Fadi El Kalach, A.E. Harper, et al.
Robotics and Computer-Integrated Manufacturing (2025) Vol. 95, pp. 103010-103010
Open Access
Comparative analysis and evaluation of ageing forecasting methods for semiconductor devices in online health monitoring
A S Jorge Villalobos, Iban Barrutia, Rafael Peña‐Alzola, et al.
Engineering Applications of Artificial Intelligence (2025) Vol. 150, pp. 110545-110545
Closed Access
Variational mode decomposition and sample entropy optimization based transformer framework for cloud resource load prediction
Jia‐Xian Zhu, Weihua Bai, Jialing Zhao, et al.
Knowledge-Based Systems (2023) Vol. 280, pp. 111042-111042
Closed Access | Times Cited: 14
How Does It Function? Characterizing Long-term Trends in Production Serverless Workloads
Artjom Joosen, Ahmed Hassan, Martin Asenov, et al.
(2023), pp. 443-458
Open Access | Times Cited: 13
Deep Learning Based Forecasting: A Case Study from the Online Fashion Industry
Manuel Kunz, Stefan Birr, Mones Raslan, et al.
Palgrave advances in the economics of innovation and technology (2023), pp. 279-311
Closed Access | Times Cited: 12
A survey on spatio-temporal series prediction with deep learning: taxonomy, applications, and future directions
Feiyan Sun, Wenning Hao, Ao Zou, et al.
Neural Computing and Applications (2024) Vol. 36, Iss. 17, pp. 9919-9943
Closed Access | Times Cited: 4
A Comparative Analysis of Machine Learning and Deep Learning Techniques for Accurate Market Price Forecasting
Olamilekan Shobayo, Sidikat Adeyemi-longe, Olusogo Popoola, et al.
Analytics (2025) Vol. 4, Iss. 1, pp. 5-5
Open Access
Wind energy forecasting with missing values within a fully conditional specification framework
Honglin Wen, Pierre Pinson, Jie Gu, et al.
International Journal of Forecasting (2023) Vol. 40, Iss. 1, pp. 77-95
Open Access | Times Cited: 11
A two-stage adversarial Transformer based approach for multivariate industrial time series anomaly detection
Junfu Chen, Dechang Pi, Xixuan Wang
Applied Intelligence (2024) Vol. 54, Iss. 5, pp. 4210-4229
Closed Access | Times Cited: 3
Evaluating the Effectiveness of Time Series Transformers for Demand Forecasting in Retail
José Manuel Oliveira, Patrícia Ramos
Mathematics (2024) Vol. 12, Iss. 17, pp. 2728-2728
Open Access | Times Cited: 3
An Advisor Neural Network framework using LSTM-based Informative Stock Analysis
Fausto Ricchiuti, Giancarlo Sperlì
Expert Systems with Applications (2024) Vol. 259, pp. 125299-125299
Open Access | Times Cited: 3
Time Series Prediction Methodology and Ensemble Model Using Real-World Data
Mintai Kim, Sung-Ju Lee, Taikyeong Jeong
Electronics (2023) Vol. 12, Iss. 13, pp. 2811-2811
Open Access | Times Cited: 8
AQIPred: A Hybrid Model for High Precision Time Specific Forecasting of Air Quality Index with Cluster Analysis
Farhana Yasmin, Md. Mehedi Hassan, Mahade Hasan, et al.
Human-Centric Intelligent Systems (2023) Vol. 3, Iss. 3, pp. 275-295
Open Access | Times Cited: 8
Physically-guided temporal diffusion transformer for long-term time series forecasting
Zeqi Ren, Jianbo Yu, Jian Huang, et al.
Knowledge-Based Systems (2024) Vol. 304, pp. 112508-112508
Closed Access | Times Cited: 2
Diversify: A General Framework for Time Series Out-of-Distribution Detection and Generalization
Lu Wang, Jindong Wang, Xinwei Sun, et al.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2024) Vol. 46, Iss. 6, pp. 4534-4550
Open Access | Times Cited: 2
Weather-Driven Solar Power Forecasting Using D-Informer: Enhancing Predictions with Climate Variables
Chenglian Ma, Rui Han, Zhao An, et al.
Energy Engineering (2024) Vol. 121, Iss. 5, pp. 1245-1261
Open Access | Times Cited: 2
Leveraging Hybrid Deep Learning Models for Enhanced Multivariate Time Series Forecasting
Amal Mahmoud, Ammar Mohammed
Neural Processing Letters (2024) Vol. 56, Iss. 5
Open Access | Times Cited: 2
Machine Learning Models Informed by Connected Mixture Components for Short- and Medium-Term Time Series Forecasting
Andrey Gorshenin, Anton L. Vilyaev
AI (2024) Vol. 5, Iss. 4, pp. 1955-1976
Open Access | Times Cited: 2
Rethinking self-supervised learning for time series forecasting: A temporal perspective
Shubao Zhao, Xinxing Zhou, Ming Jin, et al.
Knowledge-Based Systems (2024) Vol. 305, pp. 112652-112652
Closed Access | Times Cited: 2
Is Mamba effective for time series forecasting?
Zihan Wang, Fanheng Kong, Feng Shi, et al.
Neurocomputing (2024), pp. 129178-129178
Open Access | Times Cited: 2
Midwifery learning and forecasting: Predicting content demand with user-generated logs
Anna Ortiz Guitart, Ana Fernández del Río, África Periáñez, et al.
Artificial Intelligence in Medicine (2023) Vol. 138, pp. 102511-102511
Open Access | Times Cited: 6

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