Motonobu Kanagawa

11 papers and 123 indexed citations i.

Motonobu Kanagawa is a scholar working on Artificial Intelligence, Control and Systems Engineering and Computational Theory and Mathematics. According to data from OpenAlex, Motonobu Kanagawa has authored 11 papers receiving a total of 123 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Artificial Intelligence, 2 papers in Control and Systems Engineering and 2 papers in Computational Theory and Mathematics. Recurrent topics in Motonobu Kanagawa’s work include Gaussian Processes and Bayesian Inference (5 papers), Domain Adaptation and Few-Shot Learning (2 papers) and Target Tracking and Data Fusion in Sensor Networks (2 papers). Motonobu Kanagawa is often cited by papers focused on Gaussian Processes and Bayesian Inference (5 papers), Domain Adaptation and Few-Shot Learning (2 papers) and Target Tracking and Data Fusion in Sensor Networks (2 papers). Motonobu Kanagawa collaborates with scholars based in Japan, Germany and United Kingdom. Motonobu Kanagawa's co-authors include Bharath K. Sriperumbudur, Dino Sejdinović, Philipp Hennig, Kenji Fukumizu, Arthur Gretton, Simo Särkkä, Tsutomu Hirao, Tomoharu Iwata and An Chen and has published in prestigious journals such as Neural Computation, Machine Learning and Data Mining and Knowledge Discovery.