An extension of XGBoost to probabilistic modelling
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Updated
Jan 31, 2024 - Python
An extension of XGBoost to probabilistic modelling
An extension of LightGBM to probabilistic modelling
An extension of CatBoost to probabilistic modelling
A python package for semi-structured deep distributional regression
Code for the KDD 2019 workshop paper. Attention mechanism for distribution regression.
Mambular is a Python package that brings the power of Mamba architectures to tabular data, offering a suite of deep learning models for regression, classification, and distributional regression tasks.
Distributional Gradient Boosting Machines
Framework for the visualization of distributional regression models
Penalized Transformation Models in Liesel
Code of "U-Net-based Methods for the Postprocessing of Precipitation Ensemble Forecasts", Pic et al. (2024+)
Time Series based Ensemble Model Output Statistics
code for the KDD 2019 workshop paper https://arxiv.org/abs/1904.10583. Kernel mean embedding for distribution regression.
Bayesian Conditional Transformation Models by Manuel Carlan, Thomas Kneib and Nadja Klein
An extension of Py-Boost to probabilistic modelling
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