Andreas Veit

9 papers and 400 indexed citations .

Andreas Veit is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Computer Networks and Communications. According to data from OpenAlex, Andreas Veit has authored 9 papers receiving a total of 400 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Artificial Intelligence, 5 papers in Computer Vision and Pattern Recognition and 1 paper in Computer Networks and Communications. Recurrent topics in Andreas Veit’s work include Advanced Neural Network Applications (5 papers), Adversarial Robustness in Machine Learning (4 papers) and Domain Adaptation and Few-Shot Learning (2 papers). Andreas Veit is often cited by papers focused on Advanced Neural Network Applications (5 papers), Adversarial Robustness in Machine Learning (4 papers) and Domain Adaptation and Few-Shot Learning (2 papers). Andreas Veit collaborates with scholars based in United States, Germany and Switzerland. Andreas Veit's co-authors include Serge Belongie, Michael J. Wilber, Daliang Li, Daniel Gläsner, Srinadh Bhojanapalli, Ayan Chakrabarti, Thomas Unterthiner, Oliver Bähr, Elke Hattingen and Ralf Deichmann and has published in prestigious journals such as Neuroradiology, 2021 IEEE/CVF International Conference on Computer Vision (ICCV) and arXiv (Cornell University).