Geoffrey E. Hinton

28.6k total citations · 1 hit paper
24 papers, 4.5k citations indexed

About

Geoffrey E. Hinton is a scholar working on Artificial Intelligence, Signal Processing and Computer Vision and Pattern Recognition. According to data from OpenAlex, Geoffrey E. Hinton has authored 24 papers receiving a total of 4.5k indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Artificial Intelligence, 9 papers in Signal Processing and 6 papers in Computer Vision and Pattern Recognition. Recurrent topics in Geoffrey E. Hinton's work include Neural Networks and Applications (14 papers), Blind Source Separation Techniques (5 papers) and Speech Recognition and Synthesis (5 papers). Geoffrey E. Hinton is often cited by papers focused on Neural Networks and Applications (14 papers), Blind Source Separation Techniques (5 papers) and Speech Recognition and Synthesis (5 papers). Geoffrey E. Hinton collaborates with scholars based in Canada, United Kingdom and Japan. Geoffrey E. Hinton's co-authors include Tim Shallice, Steven J. Nowlan, George E. Dahl, Marc’Aurelio Ranzato, Abdelrahman Mohamed, Tony Plate, Brendan J. Frey, Toshiyuki Hanazawa, Kevin Lang and Kiyohiro Shikano and has published in prestigious journals such as Reviews of Modern Physics, Nature Neuroscience and Psychological Review.

In The Last Decade

Geoffrey E. Hinton

22 papers receiving 4.2k citations

Hit Papers

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What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Training Products of Experts by Minimizing Contrastive Divergence

2002 3.1k citations Geoffrey E. Hinton Neural Computation profile →

Peers

Countries citing papers authored by Geoffrey E. Hinton

Since Specialization

Citations

This map shows the geographic impact of Geoffrey E. Hinton's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Geoffrey E. Hinton with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Geoffrey E. Hinton more than expected).

Fields of papers citing papers by Geoffrey E. Hinton

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Geoffrey E. Hinton. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Geoffrey E. Hinton. The network helps show where Geoffrey E. Hinton may publish in the future.

Co-authorship network of co-authors of Geoffrey E. Hinton

This figure shows the co-authorship network connecting the top 25 collaborators of Geoffrey E. Hinton. A scholar is included among the top collaborators of Geoffrey E. Hinton based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Geoffrey E. Hinton. Geoffrey E. Hinton is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

#	Work	Indexed citations
1	Nobel Lecture: Boltzmann machines 2025 ·Reviews of Modern Physics ·Geoffrey E. Hinton	0
2	The Next Generation of Neural Networks 2020 ·Geoffrey E. Hinton	3
3	Phone Recognition with the Mean-Covariance Restricted Boltzmann Machine 2010 ·Neural Information Processing Systems ·George E. Dahl, Marc’Aurelio Ranzato, Abdelrahman Mohamed, Geoffrey E. Hinton	185
4	What kind of a graphical model is the brain 2005 ·International Joint Conference on Artificial Intelligence ·Geoffrey E. Hinton	30
5	Probabilistic Sequential Independent Components Analysis 2004 ·IEEE Transactions on Neural Networks ·Max Welling, Richard S. Zemel, Geoffrey E. Hinton	7
6	Phoneme recognition: neural networks vs. hidden Markov models vs. hidden Markov models 2003 ·Alexander Waibel, Toshiyuki Hanazawa, Geoffrey E. Hinton, Kiyohiro Shikano, Kevin Lang	22
7	Training Products of Experts by Minimizing Contrastive Divergence breakdown → 2002 ·Neural Computation ·Geoffrey E. Hinton	3064
8	Split and merge EM algorithm for improving Gaussian mixture density estimates 2002 ·N. Ueda, Ryoko Nakano, Zoubin Ghahramani, Geoffrey E. Hinton	13
9	Relative Density Nets: A New Way to Combine Backpropagation with HMM's 2001 ·Neural Information Processing Systems ·Andrew D. Brown, Geoffrey E. Hinton	1
10	Computation by neural networks 2000 ·Nature Neuroscience ·Geoffrey E. Hinton	13
11	Using EM for Reinforcement Learning 2000 ·Peter Dayan, Geoffrey E. Hinton	14
12	Split and Merge EM Algorithm for Improving Gaussian Mixture Density Estimates 2000 ·The Journal of VLSI Signal Processing Systems for Signal Image and Video Technology ·Naonori Ueda, Ryohei Nakano, Zoubin Ghahramani, Geoffrey E. Hinton	32
13	Learning to Parse Images 1999 ·UCL Discovery (University College London) ·Geoffrey E. Hinton, Zoubin Ghahramani, Yee Whye Teh	27
14	Variational Learning in Nonlinear Gaussian Belief Networks 1999 ·Neural Computation ·Brendan J. Frey, Geoffrey E. Hinton	47
15	Distributed representations and nested compositional structure 1994 ·Tony Plate, Geoffrey E. Hinton	84
16	Combining two methods of recognizing hand-printed digits 1992 ·Geoffrey E. Hinton, Christopher K. I. Williams, Michael Revow	4
17	Lesioning an attractor network: Investigations of acquired dyslexia. 1991 ·Psychological Review ·Geoffrey E. Hinton, Tim Shallice	486
18	Using fast weights to deblur old memories 1987 ·eScholarship (California Digital Library) ·Geoffrey E. Hinton	86
19	How Learning Can Guide Evolution. 1987 ·Complex Systems ·Geoffrey E. Hinton, Steven J. Nowlan	277
20	G-Maximization: an Unsupervised Learning Procedure \nfor Discovering Regularities 1986 ·Maynooth University ePrints and eTheses Archive (Maynooth University) ·Barak A. Pearlmutter, Geoffrey E. Hinton	19

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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