Vikas Verma

13 papers and 584 indexed citations i.

Vikas Verma is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Electrical and Electronic Engineering. According to data from OpenAlex, Vikas Verma has authored 13 papers receiving a total of 584 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Artificial Intelligence, 8 papers in Computer Vision and Pattern Recognition and 1 paper in Electrical and Electronic Engineering. Recurrent topics in Vikas Verma’s work include Domain Adaptation and Few-Shot Learning (8 papers), Adversarial Robustness in Machine Learning (8 papers) and Anomaly Detection Techniques and Applications (5 papers). Vikas Verma is often cited by papers focused on Domain Adaptation and Few-Shot Learning (8 papers), Adversarial Robustness in Machine Learning (8 papers) and Anomaly Detection Techniques and Applications (5 papers). Vikas Verma collaborates with scholars based in Finland, United States and Canada. Vikas Verma's co-authors include Juho Kannala, Alex Lamb, Yoshua Bengio, David López-Paz, Kenji Kawaguchi, Arno Solin, Jisoo Jeong, Nojun Kwak, Jian Tang and Meng Qu and has published in prestigious journals such as Neural Networks, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) and Aaltodoc (Aalto University).