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An Uncertainty-Aware ED-LSTM for Probabilistic Suffix Prediction

An Uncertainty-Aware ED-LSTM for Probabilistic Suffix Prediction

27 May 2025
Henryk Mustroph
Michel Kunkler
Stefanie Rinderle-Ma
ArXivPDFHTML

Papers citing "An Uncertainty-Aware ED-LSTM for Probabilistic Suffix Prediction"

13 / 13 papers shown
Title
What Averages Do Not Tell -- Predicting Real Life Processes with
  Sequential Deep Learning
What Averages Do Not Tell -- Predicting Real Life Processes with Sequential Deep Learning
István Ketykó
F. Mannhardt
Marwan Hassani
B. V. Dongen
AI4TS
16
10
0
19 Oct 2021
A Deep Adversarial Model for Suffix and Remaining Time Prediction of
  Event Sequences
A Deep Adversarial Model for Suffix and Remaining Time Prediction of Event Sequences
Farbod Taymouri
M. Rosa
S. Erfani
34
26
0
15 Feb 2021
A Review of Uncertainty Quantification in Deep Learning: Techniques,
  Applications and Challenges
A Review of Uncertainty Quantification in Deep Learning: Techniques, Applications and Challenges
Moloud Abdar
Farhad Pourpanah
Sadiq Hussain
Dana Rezazadegan
Li Liu
...
Xiaochun Cao
Abbas Khosravi
U. Acharya
V. Makarenkov
S. Nahavandi
BDL
UQCV
213
1,893
0
12 Nov 2020
Aleatoric and Epistemic Uncertainty in Machine Learning: An Introduction
  to Concepts and Methods
Aleatoric and Epistemic Uncertainty in Machine Learning: An Introduction to Concepts and Methods
Eyke Hüllermeier
Willem Waegeman
PER
UD
183
1,388
0
21 Oct 2019
Survey and cross-benchmark comparison of remaining time prediction
  methods in business process monitoring
Survey and cross-benchmark comparison of remaining time prediction methods in business process monitoring
I. Verenich
Marlon Dumas
M. Rosa
F. Maggi
Irene Teinemaa
AI4TS
27
150
0
08 May 2018
GradNorm: Gradient Normalization for Adaptive Loss Balancing in Deep
  Multitask Networks
GradNorm: Gradient Normalization for Adaptive Loss Balancing in Deep Multitask Networks
Zhao Chen
Vijay Badrinarayanan
Chen-Yu Lee
Andrew Rabinovich
ODL
121
1,273
0
07 Nov 2017
Deep and Confident Prediction for Time Series at Uber
Deep and Confident Prediction for Time Series at Uber
Lingxue Zhu
N. Laptev
BDL
AI4TS
117
344
0
06 Sep 2017
DeepAR: Probabilistic Forecasting with Autoregressive Recurrent Networks
DeepAR: Probabilistic Forecasting with Autoregressive Recurrent Networks
David Salinas
Valentin Flunkert
Jan Gasthaus
AI4TS
UQCV
BDL
81
2,080
0
13 Apr 2017
What Uncertainties Do We Need in Bayesian Deep Learning for Computer
  Vision?
What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision?
Alex Kendall
Y. Gal
BDL
OOD
UD
UQCV
PER
312
4,667
0
15 Mar 2017
Predicting Process Behaviour using Deep Learning
Predicting Process Behaviour using Deep Learning
Joerg Evermann
Jana-Rebecca Rehse
Peter Fettke
61
353
0
14 Dec 2016
Predictive Business Process Monitoring with LSTM Neural Networks
Predictive Business Process Monitoring with LSTM Neural Networks
Niek Tax
I. Verenich
M. Rosa
Marlon Dumas
47
444
0
07 Dec 2016
A Theoretically Grounded Application of Dropout in Recurrent Neural
  Networks
A Theoretically Grounded Application of Dropout in Recurrent Neural Networks
Y. Gal
Zoubin Ghahramani
UQCV
DRL
BDL
138
1,644
0
16 Dec 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
533
9,233
0
06 Jun 2015
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