7 citations · 19 across the 19 of their papers we have counts for
4 papers · 1 filter
Higher-Order Hit-&-Run Samplers for Linearly Constrained Densities
Richard D. Paul, Anton Stratmann, Johann F. Jadebeck +4
Markov chain Monte Carlo (MCMC) sampling of densities restricted to linearly constrained domains is an important task arising in Bayesian treatment of inverse problems in the natur…
mixdistreg: An R Package for Fitting Mixture of Experts Distributional Regression with Adaptive First-order Methods
David Rügamer
This paper presents a high-level description of the R software package mixdistreg to fit mixture of experts distributional regression models. The proposed framework is implemented…
Estimating Conditional Distributions with Neural Networks using R package deeptrafo
Lucas Kook, Philipp FM Baumann, Oliver Dürr +2
Contemporary empirical applications frequently require flexible regression models for complex response types and large tabular or non-tabular, including image or text, data. Classi…
Accelerated Componentwise Gradient Boosting using Efficient Data Representation and Momentum-based Optimization
Daniel Schalk, Bernd Bischl, David Rügamer
Componentwise boosting (CWB), also known as model-based boosting, is a variant of gradient boosting that builds on additive models as base learners to ensure interpretability. CWB…