Institution · Alphabet (United States)
Most cited papers from Alphabet (United States)
What are the most cited papers from Alphabet (United States)?
The most cited paper from Alphabet (United States) is "Deep learning" (Yann LeCun, Yoshua Bengio, Geoffrey E. Hinton, 2015), with 84,939 citations. Next come "ImageNet classification with deep convolutional neural networks" (75,634) and "Scikit-learn: Machine Learning in Python" (64,016).
Showing 50 of 56 papers. Every paper with more than 5,586 citations is listed.
| # | Paper | ||
|---|---|---|---|
| 1 | Deep learning Yann LeCun, Yoshua Bengio, Geoffrey E. Hinton · Nature | 26 May 2015 | 84,939 |
| 2 | ImageNet classification with deep convolutional neural networks Alex Krizhevsky, Ilya Sutskever, Geoffrey E. Hinton · Communications of the ACM | 24 May 2017 | 75,634 |
| 3 | Scikit-learn: Machine Learning in Python Fabián Pedregosa, Gaël Varoquaux, Alexandre Gramfort et al. · ORBi (University of Liège) | 2 Jan 2012 | 64,016 |
| 4 | Highly accurate protein structure prediction with AlphaFold John Jumper et al. · Nature | 15 Jul 2021 | 47,486 |
| 5 | Going deeper with convolutions Christian Szegedy, Wei Liu, Yangqing Jia et al. | Jun 2015 | 47,422 |
| 6 | AI-Assisted Pipeline for Dynamic Generation of Trustworthy Health Supplement Content at Scale Kefallinos, Dionysios, Alexandris, Georgios, Maras, Alexis et al. · arXiv (Cornell University) | 11 Oct 2018 | 46,030 |
| 7 | SciPy 1.0: fundamental algorithms for scientific computing in Python Pauli Virtanen et al. · Nature Methods | 3 Feb 2020 | 40,161 |
| 8 | Rethinking the Inception Architecture for Computer Vision Christian Szegedy, Vincent Vanhoucke, Sergey Ioffe et al. | Jun 2016 | 31,624 |
| 9 | Human-level control through deep reinforcement learning Volodymyr Mnih, Koray Kavukcuoglu, David Lawrence Silver et al. · Nature | 24 Feb 2015 | 31,206 |
| 10 | SSD: Single Shot MultiBox Detector Wei Liu, Dragomir Anguelov, Dumitru Erhan et al. | 16 Jan 2016 | 30,509 |
| 11 | MobileNetV2: Inverted Residuals and Linear Bottlenecks Mark Sandler, Andrew Howard, Menglong Zhu et al. | Jun 2018 | 26,808 |
| 12 | Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2 Evan K Bolyen et al. · Nature Biotechnology | 24 Jul 2019 | 25,165 |
| 13 | Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift Sergey Ioffe, Christian Szegedy · arXiv (Cornell University) | 11 Feb 2015 | 24,392 |
| 14 | Array programming with NumPy Charles R. Harris et al. · Nature | 16 Sep 2020 | 23,885 |
| 15 | DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs Liang-Chieh Chen, George Papandreou, Iasonas Kokkinos et al. · IEEE Transactions on Pattern Analysis and Machine Intelligence | 27 Apr 2017 | 22,754 |
| 16 | An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov et al. · arXiv (Cornell University) | 22 Oct 2020 | 22,044 |
| 17 | Xception: Deep Learning with Depthwise Separable Convolutions François Chollet | Jul 2017 | 19,596 |
| 18 | Array programming with NumPy Cr Harris et al. · RePEc: Research Papers in Economics | 17 Sep 2020 | 18,804 |
| 19 | MapReduce Jay B. Dean, Sanjay Ghemawat · Communications of the ACM | 2008 | 18,671 |
| 20 | Efficient Estimation of Word Representations in Vector Space Tomáš Mikolov, Kai Chen, Greg S. Corrado et al. · arXiv (Cornell University) | 16 Jan 2013 | 18,196 |
| 21 | Distributed Representations of Words and Phrases and their Compositionality Tomáš Mikolov, Ilya Sutskever, Kai Chen et al. · arXiv (Cornell University) | 16 Oct 2013 | 18,034 |
| 22 | Mastering the game of Go with deep neural networks and tree search David Lawrence Silver, Aja Huang, Chris J. Maddison et al. · Nature | 26 Jan 2016 | 16,121 |
| 23 | Accurate structure prediction of biomolecular interactions with AlphaFold 3 Josh Abramson et al. · Nature | 8 May 2024 | 15,959 |
| 24 | Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation Liang-Chieh Chen, Yukun Zhu, George Papandreou et al. · Lecture notes in computer science | 2018 | 15,130 |
| 25 | Google Earth Engine: Planetary-scale geospatial analysis for everyone Noel Gorelick, M. Hancher, Mike Dixon et al. · Remote Sensing of Environment | 6 Jul 2017 | 15,009 |
| 26 | Generative adversarial networks Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza et al. · Communications of the ACM | 22 Oct 2020 | 14,417 |
| 27 | Sequence to Sequence Learning with Neural Networks Ilya Sutskever, Oriol Vinyals, Quoc Viet Le · arXiv (Cornell University) | 10 Sep 2014 | 13,337 |
| 28 | Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning Christian Szegedy, Sergey Ioffe, Vincent Vanhoucke et al. · AAAI Publications (The Association for the Advancement of Artificial Intelligence (AAAI)) | 12 Feb 2017 | 12,801 |
| 29 | High-Resolution Global Maps of 21st-Century Forest Cover Change Matthew C. Hansen, Peter V. Potapov, Rebecca Moore et al. · Science | 14 Nov 2013 | 11,936 |
| 30 | FaceNet: A unified embedding for face recognition and clustering Florian Schroff, Dmitry Kalenichenko, James Philbin | Jun 2015 | 11,581 |
| 31 | Caffe Yangqing Jia, Evan Shelhamer, Jeff Donahue et al. | 3 Nov 2014 | 11,245 |
| 32 | Deep Neural Networks for Acoustic Modeling in Speech Recognition: The Shared Views of Four Research Groups Geoffrey E. Hinton, Li Deng, Dong Yu et al. · IEEE Signal Processing Magazine | 19 Oct 2012 | 10,453 |
| 33 | Analysis of protein-coding genetic variation in 60,706 humans Monkol Lek et al. · Nature | Aug 2016 | 10,439 |
| 34 | nnU-Net: a self-configuring method for deep learning-based biomedical image segmentation Fabian Isensee, Paul F. Jaeger, Simon A. A. Kohl et al. · Nature Methods | 7 Dec 2020 | 9,588 |
| 35 | Mastering the game of Go without human knowledge David Lawrence Silver, Julian Schrittwieser, Karen Simonyan et al. · Nature | Oct 2017 | 9,370 |
| 36 | EfficientDet: Scalable and Efficient Object Detection Mingxing Tan, Ruoming Pang, Quoc Viet Le | Jun 2020 | 9,034 |
| 37 | TensorFlow: A system for large-scale machine learning Martı́n Abadi et al. · arXiv (Cornell University) | 27 May 2016 | 8,828 |
| 38 | Adaptive Subgradient Methods for Online Learning and Stochastic Optimization John C. Duchi, Elad Hazan, Yoram Singer | 2010 | 8,604 |
| 39 | AlphaFold Protein Structure Database: massively expanding the structural coverage of protein-sequence space with high-accuracy models Mihály Váradi et al. · Nucleic Acids Research | 19 Oct 2021 | 8,593 |
| 40 | Explaining and Harnessing Adversarial Examples Ian Goodfellow, Jonathon Shlens, Christian Szegedy · arXiv (Cornell University) | 20 Dec 2014 | 8,140 |
| 41 | 3D U-Net: Learning Dense Volumetric Segmentation from Sparse Annotation Özgün Çiçek, Ahmed Abdulkadir, Soeren S. Lienkamp et al. · Lecture notes in computer science | 2016 | 7,911 |
| 42 | Development and Validation of a Deep Learning Algorithm for Detection of Diabetic Retinopathy in Retinal Fundus Photographs Varun Gulshan, Lily Peng, Marc Coram et al. · JAMA | 29 Nov 2016 | 7,873 |
| 43 | Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990–2015: a systematic analysis for the Global Burden of Disease Study 2015 Mohammad Hossein Forouzanfar et al. · The Lancet | Oct 2016 | 7,829 |
| 44 | Overcoming catastrophic forgetting in neural networks James Kirkpatrick, Razvan Pascanu, Neil C. Rabinowitz et al. · Proceedings of the National Academy of Sciences | 14 Mar 2017 | 7,777 |
| 45 | Attention Is All You Need Ashish Vaswani, Noam Shazeer, Niki Jitendra Parmar et al. | 23 Aug 2025 | 7,660 |
| 46 | A Simple Framework for Contrastive Learning of Visual Representations Ting Chen, Simon Kornblith, Mohammad Norouzi et al. · arXiv (Cornell University) | 13 Feb 2020 | 7,327 |
| 47 | Quantum supremacy using a programmable superconducting processor Frank Arute et al. · Nature | 23 Oct 2019 | 7,216 |
| 48 | Continuous control with deep reinforcement learning Timothy Lillicrap, Jonathan J. Hunt, Alexander Pritzel et al. · arXiv (Cornell University) | 22 Jul 2016 | 6,781 |
| 49 | NeRF Ben Mildenhall, Pratul P. Srinivasan, Matthew Tancik et al. · Communications of the ACM | 17 Dec 2021 | 6,590 |
| 50 | Show and tell: A neural image caption generator Oriol Vinyals, Alexander Toshev, Samy Bengio et al. | Jun 2015 | 6,460 |
Citations are OpenAlex's own counts, from its 2026-09-23 snapshot, so the ranking can differ from Google Scholar or Web of Science. A paper is listed for an institution when any of its authors gave it as an affiliation; retracted papers and papers whose citation count cannot be traced to citing works are left out, and a preprint and the article it became are shown once. Release dates are OpenAlex's: where a source gave only a month or a year, that is what is shown. How the lists are chosen.