Tijmen Blankevoort
Impact in
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- Advanced Neural Network Applications
- Advanced Image and Video Retrieval Techniques
- Multimodal Machine Learning Applications
- Artificial Intelligence top 10%
- Domain Adaptation and Few-Shot Learning
- Adversarial Robustness in Machine Learning
- Neural Networks and Applications
- Topic Modeling
Papers in
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- Advanced Neural Network Applications 12
- Advanced Image and Video Retrieval Techniques 2
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- Domain Adaptation and Few-Shot Learning 8
- Adversarial Robustness in Machine Learning 5
- Neural Networks and Applications 2
- Machine Learning and ELM 1
- Co-authors
- Markus Nagel (6 shared papers)Yash Bhalgat (1 shared paper)Nojun Kwak (1 shared paper)Jinwon Lee (1 shared paper)Max Welling (6 shared papers)Dushyant Mehta (2 shared papers)Babak Ehteshami Bejnordi (3 shared papers)Bert Moons (1 shared paper)
- Journals
- International Conference on Learning Representations (1 paper)Seoul National University Open Repository (Seoul National University) (1 paper)UvA-DARE (University of Amsterdam) (1 paper)arXiv (Cornell University) (4 papers)2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) (3 papers)
- Partner nations
- United KingdomNetherlandsSwitzerland
In The Last Decade
Tijmen Blankevoort
14 papers receiving 216 citations
Peers
Comparison fields: 5 of 54
- Computer Vision and Pattern Recognition 143
- Artificial Intelligence 126
- Computational Mathematics 1
- Media Technology 12
- Hardware and Architecture 9
Countries citing papers authored by Tijmen Blankevoort
This map shows the geographic impact of Tijmen Blankevoort'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 Tijmen Blankevoort with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tijmen Blankevoort more than expected).
Fields of papers citing papers by Tijmen Blankevoort
This network shows the impact of papers produced by Tijmen Blankevoort. 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 Tijmen Blankevoort. The network helps show where Tijmen Blankevoort may publish in the future.
Co-authors
The 19 scholars most cited alongside Tijmen Blankevoort, 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 | 2020 | 104 | |
| 2 | 2021 | 41 | |
| 3 | 2021 | 20 | |
| 4 | 2022 | 15 | |
| 5 | 2022 | 13 | |
| 6 | 2022 | 8 | |
| 7 | Batch-shaping for learning conditional channel gated networks | 2020 | 6 |
| 8 | 2023 | 5 | |
| 9 | Batch-Shaped Channel Gated Networks. | 2019 | 4 |
| 10 | 2020 | 4 | |
| 11 | 2023 | 3 | |
| 12 | Gradient 𝓁 1 Regularization for Quantization Robustness. | 2020 | 2 |
| 13 | Bayesian Bits: Unifying Quantization and Pruning | 2020 | 1 |
| 14 | 2023 | 1 |
About Tijmen Blankevoort
Tijmen Blankevoort is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Statistical and Nonlinear Physics, Electrical and Electronic Engineering and Computational Mechanics, having authored 14 papers that have together received 227 indexed citations. Recurring topics across this work include Advanced Neural Network Applications (12 papers), Domain Adaptation and Few-Shot Learning (8 papers), Adversarial Robustness in Machine Learning (5 papers), Neural Networks and Applications (2 papers), Advanced Image and Video Retrieval Techniques (2 papers), Model Reduction and Neural Networks (2 papers), Machine Learning and ELM (1 paper) and Cell Image Analysis Techniques (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (143 citations), Artificial Intelligence (126 citations), Computational Mathematics (1 citation), Media Technology (12 citations) and Hardware and Architecture (9 citations). Tijmen Blankevoort has collaborated with scholars based in United Kingdom, Netherlands and Switzerland. Frequent co-authors include Markus Nagel, Yash Bhalgat, Nojun Kwak, Jinwon Lee, Max Welling, Dushyant Mehta, Babak Ehteshami Bejnordi, Bert Moons, Giovanni Mariani and Amirhossein Habibian. Their work appears in journals such as International Conference on Learning Representations, Seoul National University Open Repository (Seoul National University), UvA-DARE (University of Amsterdam), arXiv (Cornell University) and 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).
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.