Avi Schwarzschild

6 papers and 123 indexed citations i.

Avi Schwarzschild is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Avi Schwarzschild has authored 6 papers receiving a total of 123 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Artificial Intelligence, 1 paper in Computer Vision and Pattern Recognition and 1 paper in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Avi Schwarzschild’s work include Adversarial Robustness in Machine Learning (5 papers), Anomaly Detection Techniques and Applications (3 papers) and Domain Adaptation and Few-Shot Learning (2 papers). Avi Schwarzschild is often cited by papers focused on Adversarial Robustness in Machine Learning (5 papers), Anomaly Detection Techniques and Applications (3 papers) and Domain Adaptation and Few-Shot Learning (2 papers). Avi Schwarzschild collaborates with scholars based in United States and Germany. Avi Schwarzschild's co-authors include Micah Goldblum, Tom Goldstein, Dawn Song, Chulin Xie, Bo Li, Aleksander Mądry, Xinyun Chen, Dimitris Tsipras, Jonas Geiping and Soumyadip Sengupta and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, arXiv (Cornell University) and International Conference on Machine Learning.