Geoff Pleiss

14 papers and 1.0k indexed citations i.

Geoff Pleiss has authored 14 papers that have received a total of 1.0k indexed citations. This includes 11 papers in Artificial Intelligence, 4 papers in Computer Vision and Pattern Recognition and 2 papers in Statistics and Probability. The topics of these papers are Gaussian Processes and Bayesian Inference (6 papers), Machine Learning and Data Classification (5 papers) and Neural Networks and Applications (3 papers). Geoff Pleiss is often cited by papers focused on Gaussian Processes and Bayesian Inference (6 papers), Machine Learning and Data Classification (5 papers) and Neural Networks and Applications (3 papers) and collaborates with scholars based in United States, China and Israel. Geoff Pleiss's co-authors include Kilian Q. Weinberger, Jacob R. Gardner, Andrew Gordon Wilson, Zhuang Liu and Gao Huang and has published in prestigious journals such as Proceedings of the National Academy of Sciences, IEEE Transactions on Pattern Analysis and Machine Intelligence and Journal of Hydrometeorology