Daniel L. Oberski
About
Daniel L. Oberski has authored 74 papers that have received a total of 1.8k indexed citations.
This includes 26 papers in Statistics and Probability, 25 papers in Artificial Intelligence and 16 papers in Sociology and Political Science. The topics of these papers are Statistical Methods and Bayesian Inference (15 papers), Machine Learning in Healthcare (8 papers) and Advanced Causal Inference Techniques (7 papers). Daniel L. Oberski is often cited by papers focused on Statistical Methods and Bayesian Inference (15 papers), Machine Learning in Healthcare (8 papers) and Advanced Causal Inference Techniques (7 papers) and collaborates with scholars based in The Netherlands, United Kingdom and United States. Daniel L. Oberski's co-authors include Jeroen K. Vermunt, Ayoub Bagheri, Folkert W. Asselbergs, Raoul Schram and Arjan Sammani and has published in prestigious journals such as Nature, Journal of Personality and Social Psychology and Journal of the American Statistical Association
In The Last Decade
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