Joris M. Mooij
About
Joris M. Mooij has authored 39 papers that have received a total of 2.6k indexed citations.
This includes 34 papers in Artificial Intelligence, 7 papers in Computer Networks and Communications and 7 papers in Statistics and Probability. The topics of these papers are Bayesian Modeling and Causal Inference (29 papers), Error Correcting Code Techniques (7 papers) and Machine Learning and Algorithms (7 papers). Joris M. Mooij is often cited by papers focused on Bayesian Modeling and Causal Inference (29 papers), Error Correcting Code Techniques (7 papers) and Machine Learning and Algorithms (7 papers) and collaborates with scholars based in The Netherlands, Germany and Lithuania. Joris M. Mooij's co-authors include Dominik Janzing, Bernhard Schölkopf, Jonas Peters, Hilbert J. Kappen and Tom Heskes and has published in prestigious journals such as Proceedings of the National Academy of Sciences, IEEE Transactions on Information Theory and The Annals of Statistics
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