Thomas G. Dietterich

138 papers and 11.0k indexed citations i.

About

Thomas G. Dietterich is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Computer Networks and Communications. According to data from OpenAlex, Thomas G. Dietterich has authored 138 papers receiving a total of 11.0k indexed citations (citations by other indexed papers that have themselves been cited), including 87 papers in Artificial Intelligence, 22 papers in Computer Vision and Pattern Recognition and 14 papers in Computer Networks and Communications. Recurrent topics in Thomas G. Dietterich’s work include Machine Learning and Algorithms (21 papers), Machine Learning and Data Classification (19 papers) and Reinforcement Learning in Robotics (17 papers). Thomas G. Dietterich is often cited by papers focused on Machine Learning and Algorithms (21 papers), Machine Learning and Data Classification (19 papers) and Reinforcement Learning in Robotics (17 papers). Thomas G. Dietterich collaborates with scholars based in United States, Germany and Australia. Thomas G. Dietterich's co-authors include Linda G. Shapiro, Alan Fern, Eric N. Mortensen, Prasad Tadepalli and Andrew R. Moldenke and has published in prestigious journals such as Proceedings of the IEEE, Communications of the ACM and Ecological Economics.

In The Last Decade

Fields of papers citing papers by Thomas G. Dietterich

Since Specialization
EngineeringComputer 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 Thomas G. Dietterich. Nodes represent fields, and links connect fields that are likely to share authors. The network helps show where Thomas G. Dietterich may publish in the future.

Countries citing papers authored by Thomas G. Dietterich

Since Specialization
Citations

This map shows the geographic impact of Thomas G. Dietterich'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 Thomas G. Dietterich with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Thomas G. Dietterich more than expected).

Rankless by CCL
2025