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Beyond expectation: Deep joint mean and quantile regression for
  spatio-temporal problems

Beyond expectation: Deep joint mean and quantile regression for spatio-temporal problems

27 August 2018
Filipe Rodrigues
Francisco Câmara Pereira
    AI4TS
ArXivPDFHTML

Papers citing "Beyond expectation: Deep joint mean and quantile regression for spatio-temporal problems"

19 / 19 papers shown
Title
Positional Encoder Graph Quantile Neural Networks for Geographic Data
Positional Encoder Graph Quantile Neural Networks for Geographic Data
William E. R. de Amorim
Scott A. Sisson
Thaís Rodrigues
David J. Nott
G. S. Rodrigues
35
0
0
27 Sep 2024
Uncertainty Quantification of Spatiotemporal Travel Demand with
  Probabilistic Graph Neural Networks
Uncertainty Quantification of Spatiotemporal Travel Demand with Probabilistic Graph Neural Networks
Qingyi Wang
Shenhao Wang
Dingyi Zhuang
Haris N. Koutsopoulos
Jinhua Zhao
AI4TS
21
19
0
07 Mar 2023
Mind the Gap: Modelling Difference Between Censored and Uncensored
  Electric Vehicle Charging Demand
Mind the Gap: Modelling Difference Between Censored and Uncensored Electric Vehicle Charging Demand
F. B. Hüttel
Filipe Rodrigues
Francisco Câmara Pereira
22
11
0
16 Jan 2023
Matching DNN Compression and Cooperative Training with Resources and
  Data Availability
Matching DNN Compression and Cooperative Training with Resources and Data Availability
F. Malandrino
G. Giacomo
Armin Karamzade
Marco Levorato
C. Chiasserini
50
9
0
02 Dec 2022
Nonparametric Probabilistic Regression with Coarse Learners
Nonparametric Probabilistic Regression with Coarse Learners
B. Lucena
36
0
0
28 Oct 2022
Regression modelling of spatiotemporal extreme U.S. wildfires via
  partially-interpretable neural networks
Regression modelling of spatiotemporal extreme U.S. wildfires via partially-interpretable neural networks
J. Richards
Raphael Huser
28
13
0
16 Aug 2022
Conditionally Elicitable Dynamic Risk Measures for Deep Reinforcement
  Learning
Conditionally Elicitable Dynamic Risk Measures for Deep Reinforcement Learning
Anthony Coache
S. Jaimungal
Á. Cartea
28
13
0
29 Jun 2022
Marginally calibrated response distributions for end-to-end learning in
  autonomous driving
Marginally calibrated response distributions for end-to-end learning in autonomous driving
Clara Hoffmann
Nadja Klein
18
2
0
03 Oct 2021
Deep Quantile Regression for Uncertainty Estimation in Unsupervised and
  Supervised Lesion Detection
Deep Quantile Regression for Uncertainty Estimation in Unsupervised and Supervised Lesion Detection
H. Akrami
Anand A. Joshi
Sergul Aydore
Richard M. Leahy
UQCV
39
4
0
20 Sep 2021
Deep Spatio-Temporal Forecasting of Electrical Vehicle Charging Demand
Deep Spatio-Temporal Forecasting of Electrical Vehicle Charging Demand
F. B. Hüttel
Inon Peled
Filipe Rodrigues
Francisco Câmara Pereira
28
13
0
21 Jun 2021
Temporal Latent Auto-Encoder: A Method for Probabilistic Multivariate
  Time Series Forecasting
Temporal Latent Auto-Encoder: A Method for Probabilistic Multivariate Time Series Forecasting
Nam H. Nguyen
Brian Quanz
BDL
AI4TS
149
66
0
25 Jan 2021
Generalized Quantile Loss for Deep Neural Networks
Generalized Quantile Loss for Deep Neural Networks
Dvir Ben-Or
Michael Kolomenkin
G. Shabat
UQCV
22
5
0
28 Dec 2020
On the Inclusion of Spatial Information for Spatio-Temporal Neural
  Networks
On the Inclusion of Spatial Information for Spatio-Temporal Neural Networks
Rodrigo de Medrano
J. Aznarte
33
15
0
15 Jul 2020
Deep Learning Tubes for Tube MPC
Deep Learning Tubes for Tube MPC
David D. Fan
Ali-akbar Agha-mohammadi
Evangelos A. Theodorou
35
57
0
05 Feb 2020
Marginally-calibrated deep distributional regression
Marginally-calibrated deep distributional regression
Nadja Klein
David J. Nott
M. Smith
UQCV
37
14
0
26 Aug 2019
Deep Distribution Regression
Deep Distribution Regression
Rui-Bing Li
H. Bondell
Brian J. Reich
UQCV
22
33
0
14 Mar 2019
Online Predictive Optimization Framework for Stochastic
  Demand-Responsive Transit Services
Online Predictive Optimization Framework for Stochastic Demand-Responsive Transit Services
Inon Peled
Kelvin Lee
Yu Jiang
Justin Dauwels
Francisco Câmara Pereira
29
9
0
26 Feb 2019
Convolutional LSTM Network: A Machine Learning Approach for
  Precipitation Nowcasting
Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcasting
Xingjian Shi
Zhourong Chen
Hao Wang
Dit-Yan Yeung
W. Wong
W. Woo
239
7,921
0
13 Jun 2015
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
289
9,167
0
06 Jun 2015
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