Denver Dash

34 total papers · 709 total citations
16 papers, 236 citations indexed

Denver Dash is a scholar working on Artificial Intelligence, Epidemiology and Computer Networks and Communications. According to data from OpenAlex, Denver Dash has authored 16 papers receiving a total of 236 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Artificial Intelligence, 3 papers in Epidemiology and 2 papers in Computer Networks and Communications. Recurrent topics in Denver Dash’s work include Bayesian Modeling and Causal Inference (10 papers), Anomaly Detection Techniques and Applications (5 papers) and Data-Driven Disease Surveillance (3 papers). Denver Dash is often cited by papers focused on Bayesian Modeling and Causal Inference (10 papers), Anomaly Detection Techniques and Applications (5 papers) and Data-Driven Disease Surveillance (3 papers). Denver Dash collaborates with scholars based in United States, Japan and Poland. Denver Dash's co-authors include Gregory F. Cooper, Marek J. Drużdżel, Weng‐Keen Wong, William R. Hogan, Michael M. Wagner, John Levander, Eve M. Schooler, Jaideep Chandrashekar, Abraham Bachrach and Dragos D. Margineantu and has published in prestigious journals such as SHILAP Revista de lepidopterología, Artificial Intelligence and Machine Learning.