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Probabilistic Time Series Forecasts with Autoregressive Transformation
  Models

Probabilistic Time Series Forecasts with Autoregressive Transformation Models

15 October 2021
David Rügamer
Philipp F. M. Baumann
Thomas Kneib
Torsten Hothorn
    AI4TS
ArXivPDFHTML

Papers citing "Probabilistic Time Series Forecasts with Autoregressive Transformation Models"

10 / 10 papers shown
Title
How Inverse Conditional Flows Can Serve as a Substitute for
  Distributional Regression
How Inverse Conditional Flows Can Serve as a Substitute for Distributional Regression
Lucas Kook
Chris Kolb
Philipp Schiele
Daniel Dold
Marcel Arpogaus
...
Philipp F. M. Baumann
Philipp Kopper
Tobias Pielok
Emilio Dorigatti
David Rügamer
BDL
AI4TS
34
1
0
08 May 2024
mixdistreg: An R Package for Fitting Mixture of Experts Distributional
  Regression with Adaptive First-order Methods
mixdistreg: An R Package for Fitting Mixture of Experts Distributional Regression with Adaptive First-order Methods
David Rügamer
35
0
0
04 Feb 2023
Estimating Conditional Distributions with Neural Networks using R
  package deeptrafo
Estimating Conditional Distributions with Neural Networks using R package deeptrafo
Lucas Kook
Philipp F. M. Baumann
Oliver Durr
Beate Sick
David Rügamer
24
6
0
24 Nov 2022
A review of predictive uncertainty estimation with machine learning
A review of predictive uncertainty estimation with machine learning
Hristos Tyralis
Georgia Papacharalampous
UD
UQCV
56
43
0
17 Sep 2022
Why Did This Model Forecast This Future? Closed-Form Temporal Saliency
  Towards Causal Explanations of Probabilistic Forecasts
Why Did This Model Forecast This Future? Closed-Form Temporal Saliency Towards Causal Explanations of Probabilistic Forecasts
Chirag Raman
Hayley Hung
Marco Loog
24
3
0
01 Jun 2022
Deep interpretable ensembles
Deep interpretable ensembles
Lucas Kook
Andrea Götschi
Philipp F. M. Baumann
Torsten Hothorn
Beate Sick
UQCV
30
8
0
25 May 2022
Distributional Gradient Boosting Machines
Distributional Gradient Boosting Machines
Alexander März
Thomas Kneib
AI4CE
23
7
0
02 Apr 2022
Bernstein Flows for Flexible Posteriors in Variational Bayes
Bernstein Flows for Flexible Posteriors in Variational Bayes
Oliver Durr
Stephan Hörling
Daniel Dold
Ivonne Kovylov
Beate Sick
BDL
13
4
0
11 Feb 2022
deepregression: a Flexible Neural Network Framework for Semi-Structured
  Deep Distributional Regression
deepregression: a Flexible Neural Network Framework for Semi-Structured Deep Distributional Regression
David Rügamer
Chris Kolb
Cornelius Fritz
Florian Pfisterer
Philipp Kopper
...
Dominik Thalmeier
Philipp F. M. Baumann
Lucas Kook
Nadja Klein
Christian L. Müller
BDL
16
19
0
06 Apr 2021
Simple and Scalable Predictive Uncertainty Estimation using Deep
  Ensembles
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles
Balaji Lakshminarayanan
Alexander Pritzel
Charles Blundell
UQCV
BDL
276
5,661
0
05 Dec 2016
1