Daniel Lowd

30 papers and 839 indexed citations i.

Daniel Lowd has authored 30 papers that have received a total of 839 indexed citations. This includes 28 papers in Artificial Intelligence, 4 papers in Information Systems and 4 papers in Signal Processing. The topics of these papers are Bayesian Modeling and Causal Inference (17 papers), Machine Learning and Algorithms (10 papers) and Topic Modeling (6 papers). Daniel Lowd is often cited by papers focused on Bayesian Modeling and Causal Inference (17 papers), Machine Learning and Algorithms (10 papers) and Topic Modeling (6 papers) and collaborates with scholars based in United States, Belgium and India. Daniel Lowd's co-authors include Pedro Domingos, Javid Ebrahimi, Dejing Dou, Jesse Davis and Anyi Rao and has published in prestigious journals such as Communications of the ACM, Machine Learning and Journal of Machine Learning Research