Geoffrey Cideron

3 papers and 24 indexed citations i.

Geoffrey Cideron is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Computer Networks and Communications. According to data from OpenAlex, Geoffrey Cideron has authored 3 papers receiving a total of 24 indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Artificial Intelligence, 1 paper in Computer Vision and Pattern Recognition and 1 paper in Computer Networks and Communications. Recurrent topics in Geoffrey Cideron’s work include Reinforcement Learning in Robotics (2 papers), Domain Adaptation and Few-Shot Learning (1 paper) and Multimodal Machine Learning Applications (1 paper). Geoffrey Cideron is often cited by papers focused on Reinforcement Learning in Robotics (2 papers), Domain Adaptation and Few-Shot Learning (1 paper) and Multimodal Machine Learning Applications (1 paper). Geoffrey Cideron collaborates with scholars based in United States, United Kingdom and France. Geoffrey Cideron's co-authors include Antoine Cully, Thomas Pierrot, Olivier Sigaud, Karim Beguir, Florian Strub, Olivier Pietquin, Johan Ferret, Roee Aharoni, Avinatan Hassidim and Nikola Momchev and has published in prestigious journals such as arXiv (Cornell University), Proceedings of the Genetic and Evolutionary Computation Conference and 2021 IEEE Symposium Series on Computational Intelligence (SSCI).