1 citations · 1 across the 2 of their papers we have counts for
4 papers
The Credibility Transformer
Ronald Richman, Salvatore Scognamiglio, Mario V. Wüthrich
Inspired by the large success of Transformers in Large Language Models, these architectures are increasingly applied to tabular data. This is achieved by embedding tabular data int…
LocalGLMnet: interpretable deep learning for tabular data
Ronald Richman, Mario V. Wüthrich
Deep learning models have gained great popularity in statistical modeling because they lead to very competitive regression models, often outperforming classical statistical models…
Interpreting Deep Learning Models with Marginal Attribution by Conditioning on Quantiles
M. Merz, R. Richman, T. Tsanakas +1
A vastly growing literature on explaining deep learning models has emerged. This paper contributes to that literature by introducing a global gradient-based model-agnostic method,…
Model uncertainty in claims reserving within Tweedie's compound Poisson models
Gareth W. Peters, Pavel V. Shevchenko, Mario V. Wüthrich
In this paper we examine the claims reserving problem using Tweedie's compound Poisson model. We develop the maximum likelihood and Bayesian Markov chain Monte Carlo simulation app…