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Autoregressive Quantile Flows for Predictive Uncertainty Estimation

Autoregressive Quantile Flows for Predictive Uncertainty Estimation

9 December 2021
Phillip Si
Allan Bishop
Volodymyr Kuleshov
    BDL
    UQCV
    AI4TS
ArXivPDFHTML

Papers citing "Autoregressive Quantile Flows for Predictive Uncertainty Estimation"

9 / 9 papers shown
Title
Block Diffusion: Interpolating Between Autoregressive and Diffusion Language Models
Block Diffusion: Interpolating Between Autoregressive and Diffusion Language Models
Marianne Arriola
Aaron Gokaslan
Justin T Chiu
Zhihan Yang
Zhixuan Qi
Jiaqi Han
S. Sahoo
Volodymyr Kuleshov
DiffM
72
5
0
12 Mar 2025
Quantifying Aleatoric Uncertainty of the Treatment Effect: A Novel Orthogonal Learner
Quantifying Aleatoric Uncertainty of the Treatment Effect: A Novel Orthogonal Learner
Valentyn Melnychuk
Stefan Feuerriegel
M. Schaar
CML
54
2
0
05 Nov 2024
Positional Encoder Graph Quantile Neural Networks for Geographic Data
Positional Encoder Graph Quantile Neural Networks for Geographic Data
William E. R. de Amorim
S. Sisson
Thaís Rodrigues
David J. Nott
G. S. Rodrigues
25
0
0
27 Sep 2024
Probabilistic Forecasting of Irregular Time Series via Conditional Flows
Probabilistic Forecasting of Irregular Time Series via Conditional Flows
Vijaya Krishna Yalavarthi
Randolf Scholz
Stefan Born
Lars Schmidt-Thieme
AI4TS
35
0
0
09 Feb 2024
Denoising Diffusion Variational Inference: Diffusion Models as Expressive Variational Posteriors
Denoising Diffusion Variational Inference: Diffusion Models as Expressive Variational Posteriors
Wasu Top Piriyakulkij
Yingheng Wang
Volodymyr Kuleshov
DiffM
37
1
0
05 Jan 2024
On Learning the Tail Quantiles of Driving Behavior Distributions via
  Quantile Regression and Flows
On Learning the Tail Quantiles of Driving Behavior Distributions via Quantile Regression and Flows
Jia Yu Tee
Oliver De Candido
Wolfgang Utschick
Philipp Geiger
27
0
0
22 May 2023
Estimating Regression Predictive Distributions with Sample Networks
Estimating Regression Predictive Distributions with Sample Networks
Ali Harakeh
Jordan S. K. Hu
Naiqing Guan
Steven L. Waslander
Liam Paull
BDL
UQCV
22
4
0
24 Nov 2022
Calibrated and Sharp Uncertainties in Deep Learning via Density Estimation
Calibrated and Sharp Uncertainties in Deep Learning via Density Estimation
Volodymyr Kuleshov
Shachi Deshpande
UQCV
BDL
32
33
0
14 Dec 2021
Dropout as a Bayesian Approximation: Representing Model Uncertainty in
  Deep Learning
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Y. Gal
Zoubin Ghahramani
UQCV
BDL
285
9,138
0
06 Jun 2015
1