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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:

The unreasonable effectiveness of deep learning in artificial intelligence
Terrence J. Sejnowski
Proceedings of the National Academy of Sciences (2020) Vol. 117, Iss. 48, pp. 30033-30038
Open Access | Times Cited: 319

Showing 1-25 of 319 citing articles:

Explainable Artificial Intelligence in education
Hassan Khosravi, Simon Buckingham Shum, Guanliang Chen, et al.
Computers and Education Artificial Intelligence (2022) Vol. 3, pp. 100074-100074
Open Access | Times Cited: 339
Nanoparticle synthesis assisted by machine learning
Huachen Tao, Tianyi Wu, Matteo Aldeghi, et al.
Nature Reviews Materials (2021) Vol. 6, Iss. 8, pp. 701-716
Closed Access | Times Cited: 313
A comprehensive and fair comparison of two neural operators (with practical extensions) based on FAIR data
Lu Lu, Xuhui Meng, Shengze Cai, et al.
Computer Methods in Applied Mechanics and Engineering (2022) Vol. 393, pp. 114778-114778
Open Access | Times Cited: 269
U-Net-Based Medical Image Segmentation
Xiaoxia Yin, Le Sun, Yuhan Fu, et al.
Journal of Healthcare Engineering (2022) Vol. 2022, pp. 1-16
Open Access | Times Cited: 234
De novo molecular design and generative models
Joshua Meyers, Benedek Fabian, Nathan Brown
Drug Discovery Today (2021) Vol. 26, Iss. 11, pp. 2707-2715
Open Access | Times Cited: 219
Computational models link cellular mechanisms of neuromodulation to large-scale neural dynamics
James M. Shine, Eli J. Műller, Brandon R. Munn, et al.
Nature Neuroscience (2021) Vol. 24, Iss. 6, pp. 765-776
Closed Access | Times Cited: 190
Machine learning and deep learning—A review for ecologists
Maximilian Pichler, Florian Härtig
Methods in Ecology and Evolution (2023) Vol. 14, Iss. 4, pp. 994-1016
Open Access | Times Cited: 183
Deep learning as a tool for ecology and evolution
Marek L. Borowiec, Rebecca B. Dikow, Paul B. Frandsen, et al.
Methods in Ecology and Evolution (2022) Vol. 13, Iss. 8, pp. 1640-1660
Open Access | Times Cited: 155
Spine dynamics in the brain, mental disorders and artificial neural networks
Haruo Kasai, Noam Ziv, Hitoshi Okazaki, et al.
Nature reviews. Neuroscience (2021) Vol. 22, Iss. 7, pp. 407-422
Closed Access | Times Cited: 145
A critical evaluation, challenges, and future perspectives of using artificial intelligence and emerging technologies in smart classrooms
Elenı Dimitriadou, Andreas Lanitis
Smart Learning Environments (2023) Vol. 10, Iss. 1
Open Access | Times Cited: 143
BENDR: Using Transformers and a Contrastive Self-Supervised Learning Task to Learn From Massive Amounts of EEG Data
Demetres Kostas, Stéphane Aroca-Ouellette, Frank Rudzicz
Frontiers in Human Neuroscience (2021) Vol. 15
Open Access | Times Cited: 137
Recent Advances in 2D Material Theory, Synthesis, Properties, and Applications
Yu‐Chuan Lin, Riccardo Torsi, Rehan Younas, et al.
ACS Nano (2023) Vol. 17, Iss. 11, pp. 9694-9747
Open Access | Times Cited: 125
Embodied neuromorphic intelligence
Chiara Bartolozzi, Giacomo Indiveri, Elisa Donati
Nature Communications (2022) Vol. 13, Iss. 1
Open Access | Times Cited: 113
Methods for Pruning Deep Neural Networks
Sunil Vadera, Salem Ameen
IEEE Access (2022) Vol. 10, pp. 63280-63300
Open Access | Times Cited: 110
Large Language Models and the Reverse Turing Test
Terrence J. Sejnowski
Neural Computation (2023) Vol. 35, Iss. 3, pp. 309-342
Open Access | Times Cited: 107
On the road to explainable AI in drug-drug interactions prediction: A systematic review
Thanh Hoa Vo, Ngan Nguyen, Quang Hien Kha, et al.
Computational and Structural Biotechnology Journal (2022) Vol. 20, pp. 2112-2123
Open Access | Times Cited: 93
Brain Computations and Connectivity
Edmund T. Rolls
Oxford University Press eBooks (2023)
Open Access | Times Cited: 56
Neural scaling of deep chemical models
Nathan C. Frey, Ryan Soklaski, Simon Axelrod, et al.
Nature Machine Intelligence (2023) Vol. 5, Iss. 11, pp. 1297-1305
Open Access | Times Cited: 48
Graph networks for molecular design
Rocío Mercado, Tobias Rastemo, Edvard Lindelöf, et al.
Machine Learning Science and Technology (2020) Vol. 2, Iss. 2, pp. 025023-025023
Open Access | Times Cited: 118
Replication across space and time must be weak in the social and environmental sciences
Michael F. Goodchild, Wenwen Li
Proceedings of the National Academy of Sciences (2021) Vol. 118, Iss. 35
Open Access | Times Cited: 101
Neurosurgery and artificial intelligence
Mohammad Mofatteh
AIMS neuroscience (2021) Vol. 8, Iss. 4, pp. 477-495
Open Access | Times Cited: 92
Mixed-Signal Computing for Deep Neural Network Inference
Boris Murmann
IEEE Transactions on Very Large Scale Integration (VLSI) Systems (2020) Vol. 29, Iss. 1, pp. 3-13
Open Access | Times Cited: 82
Living Things Are Not (20th Century) Machines: Updating Mechanism Metaphors in Light of the Modern Science of Machine Behavior
Joshua Bongard, Michael Levin
Frontiers in Ecology and Evolution (2021) Vol. 9
Open Access | Times Cited: 78
Artificial intelligence for clinical decision support in neurology
Mangor Pedersen, Karin Verspoor, Mark Jenkinson, et al.
Brain Communications (2020) Vol. 2, Iss. 2
Open Access | Times Cited: 70
Accuracy Assessment in Convolutional Neural Network-Based Deep Learning Remote Sensing Studies—Part 2: Recommendations and Best Practices
Aaron E. Maxwell, Timothy A. Warner, Luis Andrés Guillén
Remote Sensing (2021) Vol. 13, Iss. 13, pp. 2591-2591
Open Access | Times Cited: 69
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