Maximilian Igl
About
Maximilian Igl is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Computational Theory and Mathematics.
According to data from OpenAlex, Maximilian Igl has authored 9 papers receiving a total of 83 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Artificial Intelligence, 2 papers in Computer Vision and Pattern Recognition and 1 paper in Computational Theory and Mathematics. Recurrent topics in Maximilian Igl’s work include Reinforcement Learning in Robotics (6 papers), Domain Adaptation and Few-Shot Learning (3 papers) and Adversarial Robustness in Machine Learning (2 papers). Maximilian Igl is often cited by papers focused on Reinforcement Learning in Robotics (6 papers), Domain Adaptation and Few-Shot Learning (3 papers) and Adversarial Robustness in Machine Learning (2 papers). Maximilian Igl collaborates with scholars based in United Kingdom, United States and The Netherlands. Maximilian Igl's co-authors include Shimon Whiteson, Gregory Farquhar, Frank Wood, Tom Rainforth, Kyriacos Shiarlis, Katja Hofmann, Adam R. Kosiorek, Yee Whye Teh, Chris J. Maddison and Cheng Zhang and has published in prestigious journals such as Journal of Machine Learning Research, arXiv (Cornell University) and Neural Information Processing Systems.
In The Last Decade
Co-authorship network of co-authors of Maximilian Igl i
Fields of papers citing papers by Maximilian Igl
Since SpecializationEngineeringComputer SciencePhysics and AstronomyMathematicsEarth and Planetary SciencesEnergyEnvironmental ScienceMaterials ScienceChemical EngineeringChemistryAgricultural and Biological SciencesVeterinaryDecision SciencesArts and HumanitiesBusiness, Management and AccountingSocial SciencesPsychologyEconomics, Econometrics and FinanceHealth ProfessionsDentistryMedicineBiochemistry, Genetics and Molecular BiologyNeuroscienceNursingImmunology and MicrobiologyPharmacology, Toxicology and Pharmaceutics
This network shows the specialization of papers citing the papers produced by Maximilian Igl. Nodes represent fields, and links connect fields that are likely to share authors. The network helps show where Maximilian Igl may publish in the future.
Countries citing papers authored by Maximilian Igl
Since SpecializationCitations
This map shows the geographic impact of Maximilian Igl's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Maximilian Igl with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Maximilian Igl more than expected).
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