Karol Gregor
Impact in
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- Generative Adversarial Networks and Image Synthesis
- Advanced Image and Video Retrieval Techniques
- Image and Signal Denoising Methods
- Advanced Neural Network Applications
- Advanced Image Processing Techniques
- Artificial Intelligence top 0.5%
- Domain Adaptation and Few-Shot Learning
Papers in
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- Reinforcement Learning in Robotics 4
- Domain Adaptation and Few-Shot Learning 3
- Evolutionary Algorithms and Applications 2
- Neural Networks and Applications 2
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- Physics of Superconductivity and Magnetism 5
- Advanced Condensed Matter Physics 5
- Theoretical and Computational Physics 2
- Co-authors
- Iain Murray (1 shared paper)Hugo Larochelle (1 shared paper)Yann LeCun (1 shared paper)Daan Wierstra (5 shared papers)Ivo Danihelka (4 shared papers)Danilo Jimenez Rezende (6 shared papers)Alex Graves (1 shared paper)Y. Le Cun (2 shared papers)
- Journals
- Physical Review B (4 papers)Physical Review Letters (1 paper)International Conference on Learning Representations (1 paper)arXiv (Cornell University) (4 papers)Neural Information Processing Systems (5 papers)
- Partner nations
- United StatesUnited KingdomSwitzerland
In The Last Decade
Karol Gregor
20 papers receiving 3.7k citations
Karol Gregor's Hit Papers
Peers
Comparison fields: 5 of 165
- Computer Vision and Pattern Recognition 1.6k
- Artificial Intelligence 1.5k
- Signal Processing 313
- Media Technology 233
- Computational Mechanics 447
Countries citing papers authored by Karol Gregor
This map shows the geographic impact of Karol Gregor'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 Karol Gregor with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Karol Gregor more than expected).
Fields of papers citing papers by Karol Gregor
This network shows the impact of papers produced by Karol Gregor. 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 Karol Gregor. The network helps show where Karol Gregor may publish in the future.
Co-authors
The 25 scholars most cited alongside Karol Gregor, 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 21 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Proceedings of The 32nd International Conference on Machine Learning Hit paper breakdown → | 2015 | 1597 |
| 2 | Learning Fast Approximations of Sparse Coding Hit paper breakdown → | 2010 | 663 |
| 3 | DRAW: A Recurrent Neural Network For Image Generation Hit paper breakdown → | 2015 | 478 |
| 4 | Learning Convolutional Feature Hierarchies for Visual Recognition Hit paper breakdown → | 2010 | 328 |
| 5 | 2004 | 210 | |
| 6 | Universal Value Function Approximators | 2015 | 203 |
| 7 | 2014 | 94 | |
| 8 | 2013 | 54 | |
| 9 | Towards Conceptual Compression | 2016 | 45 |
| 10 | Structured sparse coding via lateral inhibition | 2011 | 32 |
| 11 | 2016 | 32 | |
| 12 | 2008 | 20 | |
| 13 | 2009 | 15 | |
| 14 | Shaping Belief States with Generative Environment Models for RL | 2019 | 7 |
| 15 | 2007 | 5 | |
| 16 | Variational Intrinsic Control | 2016 | 4 |
| 17 | 2006 | 3 | |
| 18 | 2018 | 2 | |
| 19 | A lattice filter model of the visual pathway | 2012 | 1 |
| 20 | Learning Dynamic State Abstractions for Model-Based Reinforcement Learning | 2018 | 1 |
About Karol Gregor
Karol Gregor is a scholar working on Artificial Intelligence, Condensed Matter Physics, Computer Vision and Pattern Recognition, Signal Processing and Electronic, Optical and Magnetic Materials, having authored 21 papers that have together received 3.8k indexed citations. Recurring topics across this work include Physics of Superconductivity and Magnetism (5 papers), Advanced Condensed Matter Physics (5 papers), Generative Adversarial Networks and Image Synthesis (5 papers), Reinforcement Learning in Robotics (4 papers), Domain Adaptation and Few-Shot Learning (3 papers), Evolutionary Algorithms and Applications (2 papers), Neural Networks and Applications (2 papers) and Theoretical and Computational Physics (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (1.6k citations), Artificial Intelligence (1.5k citations), Signal Processing (313 citations), Media Technology (233 citations) and Computational Mechanics (447 citations). Karol Gregor has collaborated with scholars based in United States, United Kingdom and Switzerland. Frequent co-authors include Iain Murray, Hugo Larochelle, Yann LeCun, Daan Wierstra, Ivo Danihelka, Danilo Jimenez Rezende, Alex Graves, Y. Le Cun, Andriy Mnih and Michaël Mathieu. Their work appears in journals such as Physical Review B, Physical Review Letters, International Conference on Learning Representations, arXiv (Cornell University) and Neural Information Processing Systems.
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.