Andreas Veit
Impact in
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- Advanced Neural Network Applications
- Generative Adversarial Networks and Image Synthesis
- Advanced Image and Video Retrieval Techniques
- Multimodal Machine Learning Applications
- Artificial Intelligence top 2%
- Domain Adaptation and Few-Shot Learning
- Machine Learning and Data Classification
- Adversarial Robustness in Machine Learning
- Anomaly Detection Techniques and Applications
Papers in ⓘ
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- Advanced Neural Network Applications 7
- Generative Adversarial Networks and Image Synthesis 3
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- Adversarial Robustness in Machine Learning 4
- Domain Adaptation and Few-Shot Learning 4
- Natural Language Processing Techniques 2
- Stochastic Gradient Optimization Techniques 2
- Co-authors
- Serge Belongie (7 shared papers)Michael J. Wilber (2 shared papers)Daniel Gläsner (4 shared papers)Ayan Chakrabarti (4 shared papers)Abhinav Gupta (1 shared paper)Ivan Krasin (1 shared paper)Gal Chechik (1 shared paper)Neil Alldrin (1 shared paper)
- Journals
- Neuroradiology (1 paper)2021 IEEE/CVF International Conference on Computer Vision (ICCV) (1 paper)International Conference on Artificial Intelligence and Statistics (2 papers)arXiv (Cornell University) (2 papers)Neural Information Processing Systems (2 papers)
- Partner nations
- United StatesGermanySwitzerland
In The Last Decade
Andreas Veit
21 papers receiving 1.2k citations
Hit Papers
Peers
Comparison fields: 5 of 122
- Computer Vision and Pattern Recognition 646
- Artificial Intelligence 613
- Media Technology 73
- Signal Processing 74
- Computer Science Applications 35
Countries citing papers authored by Andreas Veit
This map shows the geographic impact of Andreas Veit'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 Andreas Veit with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Andreas Veit more than expected).
Fields of papers citing papers by Andreas Veit
This network shows the impact of papers produced by Andreas Veit. 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 Andreas Veit. The network helps show where Andreas Veit may publish in the future.
Co-authors
The 25 scholars most cited alongside Andreas Veit, 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 | 2017 | 264 | |
| 2 | Understanding Robustness of Transformers for Image Classification Hit paper breakdown → | 2021 | 227 |
| 3 | Residual networks behave like ensembles of relatively shallow networks | 2016 | 187 |
| 4 | 2015 | 177 | |
| 5 | 2014 | 64 | |
| 6 | How To Backdoor Federated Learning. | 2018 | 56 |
| 7 | 2014 | 53 | |
| 8 | 2016 | 51 | |
| 9 | Rethinking FID: Towards a Better Evaluation Metric for Image Generation Hit paper breakdown → | 2024 | 45 |
| 10 | 2017 | 33 | |
| 11 | 2017 | 26 | |
| 12 | Why ADAM Beats SGD for Attention Models | 2019 | 23 |
| 13 | 2023 | 22 | |
| 14 | 2013 | 16 | |
| 15 | Convolutional Networks with Adaptive Computation Graphs. | 2017 | 9 |
| 16 | RankDistil: Knowledge Distillation for Ranking | 2021 | 4 |
| 17 | Why are Adaptive Methods Good for Attention Models | 2020 | 2 |
| 18 | 2015 | 2 | |
| 19 | 2015 | 2 | |
| 20 | 2024 | 1 |
About Andreas Veit
Andreas Veit is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Electrical and Electronic Engineering, Renewable Energy, Sustainability and the Environment and Computer Networks and Communications, having authored 21 papers that have together received 1.3k indexed citations. Recurring topics across this work include Advanced Neural Network Applications (7 papers), Adversarial Robustness in Machine Learning (4 papers), Smart Grid Energy Management (4 papers), Domain Adaptation and Few-Shot Learning (4 papers), Generative Adversarial Networks and Image Synthesis (3 papers), Energy Efficiency and Management (3 papers), Natural Language Processing Techniques (2 papers) and Stochastic Gradient Optimization Techniques (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (646 citations), Artificial Intelligence (613 citations), Media Technology (73 citations), Signal Processing (74 citations) and Computer Science Applications (35 citations). Andreas Veit has collaborated with scholars based in United States, Germany and Switzerland. Frequent co-authors include Serge Belongie, Michael J. Wilber, Daniel Gläsner, Ayan Chakrabarti, Abhinav Gupta, Ivan Krasin, Gal Chechik, Neil Alldrin, Daliang Li and Srinadh Bhojanapalli. Their work appears in journals such as Neuroradiology, 2021 IEEE/CVF International Conference on Computer Vision (ICCV), International Conference on Artificial Intelligence and Statistics, 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.