
OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!
If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.
Requested Article:
Statistical Foundations of Actuarial Learning and its Applications
Mario V. Wüthrich, Michael Merz
SSRN Electronic Journal (2021)
Open Access | Times Cited: 11
Mario V. Wüthrich, Michael Merz
SSRN Electronic Journal (2021)
Open Access | Times Cited: 11
Showing 11 citing articles:
LocalGLMnet: interpretable deep learning for tabular data
Ronald Richman, Mario V. Wüthrich
Scandinavian Actuarial Journal (2022) Vol. 2023, Iss. 1, pp. 71-95
Open Access | Times Cited: 23
Ronald Richman, Mario V. Wüthrich
Scandinavian Actuarial Journal (2022) Vol. 2023, Iss. 1, pp. 71-95
Open Access | Times Cited: 23
What can we learn from telematics car driving data: A survey
Guangyuan Gao, Shengwang Meng, Mario V. Wüthrich
Insurance Mathematics and Economics (2022) Vol. 104, pp. 185-199
Open Access | Times Cited: 21
Guangyuan Gao, Shengwang Meng, Mario V. Wüthrich
Insurance Mathematics and Economics (2022) Vol. 104, pp. 185-199
Open Access | Times Cited: 21
Collective reserving using individual claims data
Łukasz Delong, Mathias Lindholm, Mario V. Wüthrich
Scandinavian Actuarial Journal (2021) Vol. 2022, Iss. 1, pp. 1-28
Open Access | Times Cited: 17
Łukasz Delong, Mathias Lindholm, Mario V. Wüthrich
Scandinavian Actuarial Journal (2021) Vol. 2022, Iss. 1, pp. 1-28
Open Access | Times Cited: 17
Interpreting deep learning models with marginal attribution by conditioning on quantiles
Michael Merz, Ronald Richman, Andreas Tsanakas, et al.
Data Mining and Knowledge Discovery (2022) Vol. 36, Iss. 4, pp. 1335-1370
Open Access | Times Cited: 10
Michael Merz, Ronald Richman, Andreas Tsanakas, et al.
Data Mining and Knowledge Discovery (2022) Vol. 36, Iss. 4, pp. 1335-1370
Open Access | Times Cited: 10
Maximum weighted likelihood estimator for robust heavy-tail modelling of finite mixture models
Tsz Chai Fung
Insurance Mathematics and Economics (2022) Vol. 107, pp. 180-198
Open Access | Times Cited: 10
Tsz Chai Fung
Insurance Mathematics and Economics (2022) Vol. 107, pp. 180-198
Open Access | Times Cited: 10
EXTENDING THE LEE–CARTER MODEL WITH VARIATIONAL AUTOENCODER: A FUSION OF NEURAL NETWORK AND BAYESIAN APPROACH
A. Miyata, Naoki Matsuyama
Astin Bulletin (2022) Vol. 52, Iss. 3, pp. 789-812
Open Access | Times Cited: 7
A. Miyata, Naoki Matsuyama
Astin Bulletin (2022) Vol. 52, Iss. 3, pp. 789-812
Open Access | Times Cited: 7
Models: Overview on Predictive Models
Arthur Charpentier
Springer Actuarial (2024), pp. 59-122
Closed Access
Arthur Charpentier
Springer Actuarial (2024), pp. 59-122
Closed Access
Effective experience rating for large insurance portfolios via surrogate modeling
Sebastián Calcetero Vanegas, Andrei L. Badescu, X. Sheldon Lin
Insurance Mathematics and Economics (2024) Vol. 118, pp. 25-43
Open Access
Sebastián Calcetero Vanegas, Andrei L. Badescu, X. Sheldon Lin
Insurance Mathematics and Economics (2024) Vol. 118, pp. 25-43
Open Access
A closed-form alternative estimator for GLM with categorical explanatory variables
Alexandre Brouste, Christophe Dutang, Tom Rohmer
Communications in Statistics - Simulation and Computation (2022) Vol. 53, Iss. 5, pp. 2444-2460
Open Access | Times Cited: 2
Alexandre Brouste, Christophe Dutang, Tom Rohmer
Communications in Statistics - Simulation and Computation (2022) Vol. 53, Iss. 5, pp. 2444-2460
Open Access | Times Cited: 2
One-step closed-form estimator for generalized linear model with categorical explanatory variables
Alexandre Brouste, Christophe Dutang, Lilit Hovsepyan, et al.
Statistics and Computing (2023) Vol. 33, Iss. 6
Closed Access
Alexandre Brouste, Christophe Dutang, Lilit Hovsepyan, et al.
Statistics and Computing (2023) Vol. 33, Iss. 6
Closed Access
LocalGLMnet: interpretable deep learning for tabular data
Ronald Richman, Mario V. Wüthrich
(2021)
Closed Access
Ronald Richman, Mario V. Wüthrich
(2021)
Closed Access