Stefano Ermon

27 papers and 149 indexed citations i.

Stefano Ermon is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Computer Networks and Communications. According to data from OpenAlex, Stefano Ermon has authored 27 papers receiving a total of 149 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Artificial Intelligence, 4 papers in Computer Vision and Pattern Recognition and 4 papers in Computer Networks and Communications. Recurrent topics in Stefano Ermon’s work include Machine Learning and Algorithms (8 papers), Gaussian Processes and Bayesian Inference (6 papers) and Domain Adaptation and Few-Shot Learning (6 papers). Stefano Ermon is often cited by papers focused on Machine Learning and Algorithms (8 papers), Gaussian Processes and Bayesian Inference (6 papers) and Domain Adaptation and Few-Shot Learning (6 papers). Stefano Ermon collaborates with scholars based in United States, China and Germany. Stefano Ermon's co-authors include Bart Selman, Carla P. Gomes, Ashish Sabharwal, Mitchell McIntire, Daniel Ratner, Lucia Mirabella, Jun-Ting Hsieh, Shengjia Zhao, Stephan Eismann and Eric Wang and has published in prestigious journals such as npj Computational Materials, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) and arXiv (Cornell University).