Andrew Saxe
Impact in
- Cognitive Neuroscience top 5%
- Neural dynamics and brain function
- Neural and Behavioral Psychology Studies
- Memory and Neural Mechanisms
- Visual perception and processing mechanisms
- General Decision Sciences top 10%
Papers in
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- Neural Networks and Applications 13
- Domain Adaptation and Few-Shot Learning 7
- Stochastic Gradient Optimization Techniques 6
- Gaussian Processes and Bayesian Inference 3
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- Neural dynamics and brain function 14
- Visual perception and processing mechanisms 5
- Memory and Neural Mechanisms 4
- Neural and Behavioral Psychology Studies 4
- Co-authors
- Christopher Summerfield (7 shared papers)James L. McClelland (3 shared papers)Surya Ganguli (4 shared papers)Stephanie Nelli (2 shared papers)Andrew Y. Ng (3 shared papers)Ian Goodfellow (2 shared papers)Honglak Lee (1 shared paper)Quoc V. Le (1 shared paper)
- Journals
- Cognitive Science (4 papers)Neuron (3 papers)PLoS Computational Biology (2 papers)Journal of Field Robotics (1 paper)Nature reviews. Neuroscience (1 paper)
- Partner nations
- United KingdomUnited StatesCanada
In The Last Decade
Andrew Saxe
36 papers receiving 1.2k citations
Hit Papers
Peers
Comparison fields: 5 of 134
- Cognitive Neuroscience 485
- General Decision Sciences 37
- Artificial Intelligence 561
- Computer Vision and Pattern Recognition 352
- Computational Mathematics 8
Countries citing papers authored by Andrew Saxe
This map shows the geographic impact of Andrew Saxe'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 Andrew Saxe with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Andrew Saxe more than expected).
Fields of papers citing papers by Andrew Saxe
This network shows the impact of papers produced by Andrew Saxe. 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 Andrew Saxe. The network helps show where Andrew Saxe may publish in the future.
Co-authors
The 25 scholars most cited alongside Andrew Saxe, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 39 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | If deep learning is the answer, what is the question? Hit paper breakdown → | 2020 | 208 |
| 2 | Measuring Invariances in Deep Networks | 2009 | 188 |
| 3 | On Random Weights and Unsupervised Feature Learning | 2011 | 165 |
| 4 | Exact solutions to the nonlinear dynamics of learning in deep linear neural networks | 2014 | 117 |
| 5 | 2010 | 102 | |
| 6 | 2019 | 100 | |
| 7 | 2022 | 90 | |
| 8 | Qualitatively characterizing neural network optimization problems | 2015 | 54 |
| 9 | 2019 | 35 | |
| 10 | 2018 | 30 | |
| 11 | 2023 | 29 | |
| 12 | Unsupervised learning models of primary cortical receptive fields and receptive field plasticity | 2011 | 27 |
| 13 | 2023 | 18 | |
| 14 | 2023 | 18 | |
| 15 | Multitasking Capability Versus Learning Efficiency in Neural Network Architectures. | 2017 | 15 |
| 16 | 2022 | 15 | |
| 17 | 2023 | 9 | |
| 18 | 2023 | 9 | |
| 19 | 2019 | 9 | |
| 20 | Hierarchy Through Composition with Multitask LMDPs | 2017 | 8 |
About Andrew Saxe
Andrew Saxe is a scholar working on Artificial Intelligence, Cognitive Neuroscience, Computer Vision and Pattern Recognition, Statistical and Nonlinear Physics and Cellular and Molecular Neuroscience, having authored 39 papers that have together received 1.3k indexed citations. Recurring topics across this work include Neural dynamics and brain function (14 papers), Neural Networks and Applications (13 papers), Domain Adaptation and Few-Shot Learning (7 papers), Stochastic Gradient Optimization Techniques (6 papers), Visual perception and processing mechanisms (5 papers), Memory and Neural Mechanisms (4 papers), Neural and Behavioral Psychology Studies (4 papers) and Gaussian Processes and Bayesian Inference (3 papers). The work is most often cited by research in Cognitive Neuroscience (485 citations), General Decision Sciences (37 citations), Artificial Intelligence (561 citations), Computer Vision and Pattern Recognition (352 citations) and Computational Mathematics (8 citations). Andrew Saxe has collaborated with scholars based in United Kingdom, United States and Canada. Frequent co-authors include Christopher Summerfield, James L. McClelland, Surya Ganguli, Stephanie Nelli, Andrew Y. Ng, Ian Goodfellow, Honglak Lee, Quoc V. Le, Bipin Suresh and Pang Wei Koh. Their work appears in journals such as Cognitive Science, Neuron, PLoS Computational Biology, Journal of Field Robotics and Nature reviews. Neuroscience.
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.