Machine Learning with High-Cardinality Categorical Features in Actuarial Applications

30 January 2023

Papers citing "Machine Learning with High-Cardinality Categorical Features in Actuarial Applications"

9 / 9 papers shown

Title
Deep Neural Networks and Tabular Data: A Survey V. Borisov Tobias Leemann Kathrin Seßler Johannes Haug Martin Pawelczyk Gjergji Kasneci LMTD 112 696 0 05 Oct 2021
Latent Gaussian Model Boosting Fabio Sigrist AI4CE 18 23 0 19 May 2021
Hands-on Bayesian Neural Networks -- a Tutorial for Deep Learning Users Laurent Valentin Jospin Wray Buntine F. Boussaïd Hamid Laga Bennamoun OOD BDL UQCV 86 629 0 14 Jul 2020
Boosting insights in insurance tariff plans with tree-based machine learning methods Roel Henckaerts Marie-Pier Côté Katrien Antonio Roel Verbelen 44 85 0 12 Apr 2019
Similarity encoding for learning with dirty categorical variables Patricio Cerda Gaël Varoquaux Balázs Kégl CML 57 206 0 04 Jun 2018
Advances in Variational Inference Cheng Zhang Judith Butepage Hedvig Kjellström Stephan Mandt BDL 182 694 0 15 Nov 2017
Evaluating probabilistic forecasts with scoringRules Alexander I. Jordan Fabian Kruger Sebastian Lerch AI4TS 180 242 0 14 Sep 2017
Variational Inference: A Review for Statisticians David M. Blei A. Kucukelbir Jon D. McAuliffe BDL 289 4,807 0 04 Jan 2016
Weight Uncertainty in Neural Networks Charles Blundell Julien Cornebise Koray Kavukcuoglu Daan Wierstra UQCV BDL 192 1,892 0 20 May 2015