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Distributional Random Forests: Heterogeneity Adjustment and Multivariate
  Distributional Regression

Distributional Random Forests: Heterogeneity Adjustment and Multivariate Distributional Regression

29 May 2020
Domagoj Cevid
Loris Michel
Jeffrey Näf
N. Meinshausen
Peter Buhlmann
ArXivPDFHTML

Papers citing "Distributional Random Forests: Heterogeneity Adjustment and Multivariate Distributional Regression"

11 / 11 papers shown
Title
Characterization and Greedy Learning of Gaussian Structural Causal Models under Unknown Interventions
Characterization and Greedy Learning of Gaussian Structural Causal Models under Unknown Interventions
Juan L. Gamella
Armeen Taeb
C. Heinze-Deml
Peter Buhlmann
CML
91
7
0
13 Mar 2025
Model Free Prediction with Uncertainty Assessment
Model Free Prediction with Uncertainty Assessment
Yuling Jiao
Lican Kang
Jin Liu
Heng Peng
Heng Zuo
DiffM
34
0
0
21 May 2024
Copula Approximate Bayesian Computation Using Distribution Random
  Forests
Copula Approximate Bayesian Computation Using Distribution Random Forests
G. Karabatsos
37
1
0
28 Feb 2024
$\texttt{causalAssembly}$: Generating Realistic Production Data for
  Benchmarking Causal Discovery
causalAssembly\texttt{causalAssembly}causalAssembly: Generating Realistic Production Data for Benchmarking Causal Discovery
Konstantin Göbler
Tobias Windisch
Mathias Drton
T. Pychynski
Steffen Sonntag
Martin Roth
CML
70
9
0
19 Jun 2023
An Efficient Doubly-Robust Test for the Kernel Treatment Effect
An Efficient Doubly-Robust Test for the Kernel Treatment Effect
Diego Martinez-Taboada
Aaditya Ramdas
Edward H. Kennedy
OOD
18
5
0
26 Apr 2023
A new methodology to predict the oncotype scores based on
  clinico-pathological data with similar tumor profiles
A new methodology to predict the oncotype scores based on clinico-pathological data with similar tumor profiles
Z. A. Masry
Romain Pic
Clément Dombry
Chrisine Devalland
19
6
0
13 Mar 2023
Confidence and Uncertainty Assessment for Distributional Random Forests
Confidence and Uncertainty Assessment for Distributional Random Forests
Jeffrey Näf
Corinne Emmenegger
Peter Buhlmann
N. Meinshausen
30
3
0
11 Feb 2023
Stone's theorem for distributional regression in Wasserstein distance
Stone's theorem for distributional regression in Wasserstein distance
Clément Dombry
Thibault Modeste
Romain Pic
8
4
0
02 Feb 2023
Distributional regression and its evaluation with the CRPS: Bounds and
  convergence of the minimax risk
Distributional regression and its evaluation with the CRPS: Bounds and convergence of the minimax risk
Romain Pic
Clément Dombry
Philippe Naveau
Maxime Taillardat
11
5
0
09 May 2022
Minimax Optimal Conditional Density Estimation under Total Variation
  Smoothness
Minimax Optimal Conditional Density Estimation under Total Variation Smoothness
Michael Li
Matey Neykov
Sivaraman Balakrishnan
15
9
0
12 Mar 2021
ranger: A Fast Implementation of Random Forests for High Dimensional
  Data in C++ and R
ranger: A Fast Implementation of Random Forests for High Dimensional Data in C++ and R
Marvin N. Wright
A. Ziegler
93
2,731
0
18 Aug 2015
1