Standout Papers

Deep learning 1986 2026 1999 2012 45.1k
  1. Deep learning (2015)
    Yann LeCun, Yoshua Bengio et al. Nature
  2. ImageNet classification with deep convolutional neural networks (2017)
    Alex Krizhevsky, Ilya Sutskever et al. Communications of the ACM
  3. Visualizing Data using t-SNE (2008)
    Laurens van der Maaten, Geoffrey E. Hinton Journal of Machine Learning Research
  4. Dropout: a simple way to prevent neural networks from overfitting (2014)
    Nitish Srivastava, Geoffrey E. Hinton et al. Journal of Machine Learning Research
  5. Learning representations by back-propagating errors (1986)
    David E. Rumelhart, Geoffrey E. Hinton et al. Nature
  6. Reducing the Dimensionality of Data with Neural Networks (2006)
    Geoffrey E. Hinton, Ruslan Salakhutdinov Science
  7. A Fast Learning Algorithm for Deep Belief Nets (2006)
    Geoffrey E. Hinton, Simon Osindero et al. Neural Computation
  8. Rectified Linear Units Improve Restricted Boltzmann Machines (2010)
    Vinod Nair, Geoffrey E. Hinton International Conference on Machine Learning
  9. Deep Neural Networks for Acoustic Modeling in Speech Recognition: The Shared Views of Four Research Groups (2012)
    Geoffrey E. Hinton, Li Deng et al. IEEE Signal Processing Magazine
  10. Adaptive Mixtures of Local Experts (1991)
    Robert A. Jacobs, Michael I. Jordan et al. Neural Computation
  11. A Learning Algorithm for Boltzmann Machines* (1985)
    David H. Ackley, Geoffrey E. Hinton et al. Cognitive Science
  12. On the importance of initialization and momentum in deep learning (2013)
    Ilya Sutskever, James Martens et al. International Conference on Machine Learning
  13. Phoneme recognition using time-delay neural networks (1989)
    Alexander Waibel, Toshiyuki Hanazawa et al. IEEE Transactions on Acoustics Speech and Signal Processing
  14. Neighbourhood Components Analysis (2004)
    Jacob Goldberger, Geoffrey E. Hinton et al. Neural Information Processing Systems
  15. Acoustic Modeling Using Deep Belief Networks (2011)
    Abdelrahman Mohamed, George E. Dahl et al. IEEE Transactions on Audio Speech and Language Processing
  16. Connectionist learning procedures (1989)
    Geoffrey E. Hinton Artificial Intelligence
  17. Deep Boltzmann machines (2009)
    Ruslan Salakhutdinov, Geoffrey E. Hinton International Conference on Artificial Intelligence and Statistics
  18. Stochastic Neighbor Embedding (2002)
    Geoffrey E. Hinton, Sam T. Roweis Neural Information Processing Systems
  19. Deep Neural Networks for Acoustic Modeling in Speech Recognition (2012)
    Geoffrey E. Hinton, Li Deng et al. IEEE Signal Processing Magazine
  20. The Helmholtz Machine (1995)
    Peter Dayan, Geoffrey E. Hinton et al. Neural Computation
  21. Parallel models of associative memory (1981)
    Geoffrey E. Hinton, James A. Anderson CERN Document Server (European Organization for Nuclear Research)
  22. Semantic hashing (2008)
    Ruslan Salakhutdinov, Geoffrey E. Hinton International Journal of Approximate Reasoning
  23. Autoencoders, Minimum Description Length and Helmholtz Free Energy (1993)
    Geoffrey E. Hinton, Richard S. Zemel Neural Information Processing Systems
  24. Learning multiple layers of representation (2007)
    Geoffrey E. Hinton Trends in Cognitive Sciences
  25. Deep belief networks (2009)
    Geoffrey E. Hinton Scholarpedia
  26. The "Wake-Sleep" Algorithm for Unsupervised Neural Networks (1995)
    Geoffrey E. Hinton, Peter Dayan et al. Science
  27. Classical and Bayesian Inference in Neuroimaging: Theory (2002)
    Karl Friston, W.D. Penny et al. NeuroImage
  28. A general framework for parallel distributed processing (1986)
    D. E. Rumelhart, Geoffrey E. Hinton et al. MIT Press eBooks
  29. Generating Text with Recurrent Neural Networks (2011)
    Ilya Sutskever, James Martens et al. International Conference on Machine Learning
  30. Backpropagation and the brain (2020)
    Timothy Lillicrap, Adam Santoro et al. Nature reviews. Neuroscience
  31. Deep Learning—A Technology With the Potential to Transform Health Care (2018)
    Geoffrey E. Hinton JAMA
  32. A learning algorithm for boltzmann machines (1985)
    David H. Ackley, Geoffrey E. Hinton et al. Cognitive Science
  33. Learning distributed representations of concepts. (1989)
    Geoffrey E. Hinton eScholarship (California Digital Library)
  34. Simplifying Neural Networks by Soft Weight-Sharing (1992)
    Steven J. Nowlan, Geoffrey E. Hinton Neural Computation
  35. How Neural Networks Learn from Experience (1992)
    Geoffrey E. Hinton Scientific American
  36. A Scalable Hierarchical Distributed Language Model (2008)
    Andriy Mnih, Geoffrey E. Hinton UCL Discovery (University College London)
  37. Zero-Shot Learning with Semantic Output Codes (2009)
    Mark Palatucci, Dean Pomerleau et al. Figshare
  38. Deep learning for AI (2021)
    Yoshua Bengio, Yann LeCun et al. Communications of the ACM
  39. Matrix capsules with EM routing (2018)
    Geoffrey E. Hinton, Sara Sabour et al. International Conference on Learning Representations
  40. An Efficient Learning Procedure for Deep Boltzmann Machines (2012)
    Ruslan Salakhutdinov, Geoffrey E. Hinton Neural Computation
  41. On Contrastive Divergence Learning. (2005)
    Miguel Á. Carreira-Perpiñán, Geoffrey E. Hinton International Conference on Artificial Intelligence and Statistics
  42. A time-delay neural network architecture for isolated word recognition (1990)
    Kevin Lang, Alex Waibel et al. Neural Networks
  43. Application of Deep Belief Networks for Natural Language Understanding (2014)
    Ruhi Sarikaya, Geoffrey E. Hinton et al. IEEE/ACM Transactions on Audio Speech and Language Processing
  44. Replicated Softmax: an Undirected Topic Model (2009)
    Geoffrey E. Hinton, Ruslan Salakhutdinov Neural Information Processing Systems
  45. Visualizing non-metric similarities in multiple maps (2011)
    Laurens van der Maaten, Geoffrey E. Hinton Machine Learning
  46. Using very deep autoencoders for content-based image retrieval. (2011)
    Alex Krizhevsky, Geoffrey E. Hinton The European Symposium on Artificial Neural Networks
  47. Learning to Label Aerial Images from Noisy Data (2012)
    Volodymyr Mnih, Geoffrey E. Hinton International Conference on Machine Learning

Immediate Impact

16 by Nobel laureates 48 from Science/Nature 134 standout
Sub-graph 1 of 17

Citing Papers

Accurate medium-range global weather forecasting with 3D neural networks
2023 StandoutNature
11 TOPS photonic convolutional accelerator for optical neural networks
2021 StandoutNature
70 intermediate papers

Works of Geoffrey E. Hinton being referenced

ImageNet classification with deep convolutional neural networks
2017 Standout
Deep learning
2015 StandoutNature
and 27 more

Author Peers

Author Last Decade Papers Cites
Geoffrey E. Hinton 68735 53749 15527 17348 197 191.0k
Yoshua Bengio 48245 36948 8656 13039 298 127.8k
Yann LeCun 32356 28495 5620 10338 101 94.7k
Vladimir Vapnik 36800 23069 7428 7716 69 107.3k
Xiangyu Zhang 32544 55758 5631 6511 121 107.1k
Kaiming He 41209 91554 6366 8804 23 159.4k
Jian Sun 30878 50466 5286 6039 46 98.5k
Leo Breiman 33402 10635 5237 6042 91 136.3k
Robert Tibshirani 26631 12351 5474 4416 380 181.1k
Jürgen Schmidhuber 27051 13630 6537 10702 160 72.7k
Trevor Hastie 24188 11405 4542 3721 272 152.2k

All Works

Loading papers...

Rankless by CCL
2026