GE Hinton
Impact in
- Signal Processing top 5%
- Blind Source Separation Techniques
- Speech and Audio Processing
- Artificial Intelligence top 5%
- Bayesian Methods and Mixture Models
- Neural Networks and Applications
- Gaussian Processes and Bayesian Inference
- Target Tracking and Data Fusion in Sensor Networks
Papers in
-
- Neural Networks and Applications 3
- Gaussian Processes and Bayesian Inference 1
- Bayesian Methods and Mixture Models 1
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- Fractal and DNA sequence analysis 1
- Protein Structure and Dynamics 1
- Co-authors
- Zoubin Ghahramani (1 shared paper)Zoubin Ghahramani (2 shared papers)Russ R. Salakhutdinov (1 shared paper)Andriy Mnih (1 shared paper)Max Welling (1 shared paper)Simon Osindero (1 shared paper)Peter Dayan (2 shared papers)Grigori Yourganov (1 shared paper)
- Journals
- NeuroImage (1 paper)MPG.PuRe (Max Planck Society) (1 paper)Cambridge University Engineering Department Publications Database (2 papers)Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005. (1 paper)UCL Discovery (University College London) (1 paper)
- Partner nations
- Canada
In The Last Decade
GE Hinton
9 papers receiving 723 citations
Peers
Comparison fields: 5 of 95
- Signal Processing 191
- Artificial Intelligence 410
- Computer Vision and Pattern Recognition 212
- Statistics and Probability 69
- Computational Mathematics 3
Countries citing papers authored by GE Hinton
This map shows the geographic impact of GE 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 GE Hinton with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites GE Hinton more than expected).
Fields of papers citing papers by GE Hinton
This network shows the impact of papers produced by GE 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 GE Hinton. The network helps show where GE Hinton may publish in the future.
Co-authors
The 11 scholars most cited alongside GE Hinton, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | The EM algorithm for mixtures of factor analyzers | 1996 | 384 |
| 2 | Parameter estimation for linear dynamical systems | 1996 | 338 |
| 3 | The delve manual | 1996 | 36 |
| 4 | Supporting Online Material for Reducing the Dimensionality of Data with Neural Networks | 2006 | 16 |
| 5 | A New View of ICA | 2001 | 11 |
| 6 | 2006 | 8 | |
| 7 | The Helmholtz Machine Through Time | 1995 | 5 |
| 8 | 2009 | 3 | |
| 9 | Using neural networks to learn intractable generative models | 1994 | 1 |
About GE Hinton
GE Hinton is a scholar working on Artificial Intelligence, Molecular Biology, Control and Systems Engineering, Statistical and Nonlinear Physics and Signal Processing, having authored 9 papers that have together received 802 indexed citations. Recurring topics across this work include Neural Networks and Applications (3 papers), Blind Source Separation Techniques (1 paper), Advanced Control Systems Optimization (1 paper), Scientific Research and Discoveries (1 paper), Gaussian Processes and Bayesian Inference (1 paper), Fractal and DNA sequence analysis (1 paper), Protein Structure and Dynamics (1 paper) and Bayesian Methods and Mixture Models (1 paper). The work is most often cited by research in Signal Processing (191 citations), Artificial Intelligence (410 citations), Computer Vision and Pattern Recognition (212 citations), Statistics and Probability (69 citations) and Computational Mathematics (3 citations). GE Hinton has collaborated with scholars based in Canada. Frequent co-authors include Zoubin Ghahramani, Zoubin Ghahramani, Russ R. Salakhutdinov, Andriy Mnih, Max Welling, Simon Osindero, Peter Dayan, Grigori Yourganov, Tanya Schmah and Stephen C. Strother. Their work appears in journals such as NeuroImage, MPG.PuRe (Max Planck Society), Cambridge University Engineering Department Publications Database, Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005. and UCL Discovery (University College London).
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.