Roger Grosse
Impact in
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- Advanced Image and Video Retrieval Techniques
- Advanced Neural Network Applications
- Generative Adversarial Networks and Image Synthesis
- Advanced Vision and Imaging
- Image Enhancement Techniques
Papers in
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- Neural Networks and Applications 6
- Adversarial Robustness in Machine Learning 5
- Stochastic Gradient Optimization Techniques 5
- Domain Adaptation and Few-Shot Learning 3
- Reinforcement Learning in Robotics 3
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- Advanced Neural Network Applications 8
- Generative Adversarial Networks and Image Synthesis 7
- Co-authors
- Andrew Y. Ng (3 shared papers)Rajesh Ranganath (2 shared papers)Honglak Lee (2 shared papers)William T. Freeman (2 shared papers)Micah K. Johnson (1 shared paper)Edward H. Adelson (1 shared paper)Rajat Raina (1 shared paper)James Martens (4 shared papers)
- Journals
- Communications of the ACM (1 paper)Avian Conservation and Ecology (1 paper)Uncertainty in Artificial Intelligence (1 paper)Proceedings of the AAAI Conference on Artificial Intelligence (1 paper)International Conference on Machine Learning (4 papers)
- Partner nations
- CanadaUnited StatesUnited Kingdom
In The Last Decade
Roger Grosse
35 papers receiving 2.5k citations
Roger Grosse's Hit Papers
Peers
Comparison fields: 5 of 139
- Computer Vision and Pattern Recognition 1.5k
- Computer Graphics and Computer-Aided Design 131
- Artificial Intelligence 1.1k
- Signal Processing 300
- Media Technology 215
Countries citing papers authored by Roger Grosse
This map shows the geographic impact of Roger Grosse'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 Roger Grosse with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Roger Grosse more than expected).
Fields of papers citing papers by Roger Grosse
This network shows the impact of papers produced by Roger Grosse. 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 Roger Grosse. The network helps show where Roger Grosse may publish in the future.
Co-authors
The 25 scholars most cited alongside Roger Grosse, 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 37 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Convolutional deep belief networks for scalable unsupervised learning of hierarchical representations Hit paper breakdown → | 2009 | 1535 |
| 2 | 2009 | 270 | |
| 3 | 2011 | 261 | |
| 4 | Shift-invariant sparse coding for audio classification | 2007 | 117 |
| 5 | 2014 | 70 | |
| 6 | The Reversible Residual Network: Backpropagation Without Storing Activations | 2017 | 66 |
| 7 | Understanding Posterior Collapse in Generative Latent Variable Models | 2019 | 40 |
| 8 | 2020 | 40 | |
| 9 | Optimizing Neural Networks with Kronecker-factored Approximate Curvature | 2015 | 29 |
| 10 | Discovering and Exploiting Additive Structure for Bayesian Optimization | 2017 | 29 |
| 11 | Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation | 2017 | 27 |
| 12 | Distributed Second-Order Optimization using Kronecker-Factored Approximations | 2017 | 24 |
| 13 | Scaling up Natural Gradient by Sparsely Factorizing the Inverse Fisher Matrix | 2015 | 19 |
| 14 | Isolating Sources of Disentanglement in Variational Autoencoders. | 2018 | 16 |
| 15 | 2015 | 13 | |
| 16 | {Accurate and conservative estimates of MRF log-likelihood using reverse annealing} | 2015 | 12 |
| 17 | 2019 | 12 | |
| 18 | 2012 | 12 | |
| 19 | 2019 | 11 | |
| 20 | 2016 | 11 |
About Roger Grosse
Roger Grosse is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Signal Processing, Statistical and Nonlinear Physics and Computational Mechanics, having authored 37 papers that have together received 2.7k indexed citations. Recurring topics across this work include Advanced Neural Network Applications (8 papers), Generative Adversarial Networks and Image Synthesis (7 papers), Neural Networks and Applications (6 papers), Adversarial Robustness in Machine Learning (5 papers), Stochastic Gradient Optimization Techniques (5 papers), Domain Adaptation and Few-Shot Learning (3 papers), Reinforcement Learning in Robotics (3 papers) and Music and Audio Processing (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (1.5k citations), Computer Graphics and Computer-Aided Design (131 citations), Artificial Intelligence (1.1k citations), Signal Processing (300 citations) and Media Technology (215 citations). Roger Grosse has collaborated with scholars based in Canada, United States and United Kingdom. Frequent co-authors include Andrew Y. Ng, Rajesh Ranganath, Honglak Lee, William T. Freeman, Micah K. Johnson, Edward H. Adelson, Rajat Raina, James Martens, David Duvenaud and Jimmy Ba. Their work appears in journals such as Communications of the ACM, Avian Conservation and Ecology, Uncertainty in Artificial Intelligence, Proceedings of the AAAI Conference on Artificial Intelligence and International Conference on Machine Learning.
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.