Motonobu Kanagawa

11 papers and 116 indexed citations i.

Motonobu Kanagawa is a scholar working on Artificial Intelligence, Numerical Analysis and Control and Systems Engineering. According to data from OpenAlex, Motonobu Kanagawa has authored 11 papers receiving a total of 116 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Artificial Intelligence, 2 papers in Numerical Analysis and 2 papers in Control and Systems Engineering. 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 Kenji Fukumizu, Bharath K. Sriperumbudur, Arthur Gretton, Tsutomu Hirao and An Chen and has published in prestigious journals such as Neural Computation, Machine Learning and Data Mining and Knowledge Discovery.