5 citations · 5 across the 10 of their papers we have counts for
3 papers · 1 filter
Topics in the Haystack: Extracting and Evaluating Topics beyond Coherence
Anton Thielmann, Quentin Seifert, Arik Reuter +2
Extracting and identifying latent topics in large text corpora has gained increasing importance in Natural Language Processing (NLP). Most models, whether probabilistic models simi…
Prediction-based Variable Selection for Component-wise Gradient Boosting
Sophie Potts, Elisabeth Bergherr, Constantin Reinke +1
Model-based component-wise gradient boosting is a popular tool for data-driven variable selection. In order to improve its prediction and selection qualities even further, several…
"Spatial Joint Models through Bayesian Structured Piece-wise Additive Joint Modelling for Longitudinal and Time-to-Event Data"
Anja Rappl, Thomas Kneib, Stefan Lang +1
Joint models for longitudinal and time-to-event data have seen many developments in recent years. Though spatial joint models are still rare and the traditional proportional hazard…