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XGBoostLSS -- An extension of XGBoost to probabilistic forecasting
v1v2v3v4 (latest)

XGBoostLSS -- An extension of XGBoost to probabilistic forecasting

6 July 2019
Alexander März
    AI4TS
ArXiv (abs)PDFHTML

Papers citing "XGBoostLSS -- An extension of XGBoost to probabilistic forecasting"

8 / 8 papers shown
TabResFlow: A Normalizing Spline Flow Model for Probabilistic Univariate Tabular Regression
TabResFlow: A Normalizing Spline Flow Model for Probabilistic Univariate Tabular Regression
Kiran Madhusudhanan
Vijaya Krishna Yalavarthi
Jonas Sonntag
Ilia Koloiarov
Lars Schmidt-Thieme
172
0
0
23 Aug 2025
Mambular: A Sequential Model for Tabular Deep Learning
Mambular: A Sequential Model for Tabular Deep Learning
Anton Thielmann
Manish Kumar
Christoph Weisser
Arik Reuter
Benjamin Säfken
Soheila Samiee
MambaLMTD
472
19
0
12 Aug 2024
Unmasking Trees for Tabular Data
Unmasking Trees for Tabular Data
Calvin McCarter
541
5
0
08 Jul 2024
Forecasting with Hyper-Trees
Forecasting with Hyper-Trees
Alexander März
Kashif Rasul
551
0
0
13 May 2024
Tree-based Forecasting of Day-ahead Solar Power Generation from Granular
  Meteorological Features
Tree-based Forecasting of Day-ahead Solar Power Generation from Granular Meteorological FeaturesData Science in Science (DSS), 2023
Nick Berlanger
Noah van Ophoven
Tim Verdonck
Ines Wilms
238
0
0
30 Nov 2023
TreeFlow: Going beyond Tree-based Gaussian Probabilistic Regression
TreeFlow: Going beyond Tree-based Gaussian Probabilistic RegressionEuropean Conference on Artificial Intelligence (ECAI), 2022
Patryk Wielopolski
Maciej Ziȩba
UQCV
274
3
0
08 Jun 2022
M5 Competition Uncertainty: Overdispersion, distributional forecasting,
  GAMLSS and beyond
M5 Competition Uncertainty: Overdispersion, distributional forecasting, GAMLSS and beyondInternational Journal of Forecasting (IJF), 2021
F. Ziel
266
16
0
14 Jul 2021
CatBoostLSS -- An extension of CatBoost to probabilistic forecasting
CatBoostLSS -- An extension of CatBoost to probabilistic forecasting
Alexander März
AI4TS
229
10
0
04 Jan 2020
1
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