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XNAP: Making LSTM-based Next Activity Predictions Explainable by Using
  LRP

XNAP: Making LSTM-based Next Activity Predictions Explainable by Using LRP

18 August 2020
Sven Weinzierl
Sandra Zilker
Jens Brunk
K. Revoredo
Martin Matzner
J. Becker
ArXivPDFHTML

Papers citing "XNAP: Making LSTM-based Next Activity Predictions Explainable by Using LRP"

6 / 6 papers shown
Title
Explain, Adapt and Retrain: How to improve the accuracy of a PPM
  classifier through different explanation styles
Explain, Adapt and Retrain: How to improve the accuracy of a PPM classifier through different explanation styles
Williams Rizzi
Chiara Di Francescomarino
Chiara Ghidini
F. Maggi
21
0
0
27 Mar 2023
Counterfactual Explanations for Predictive Business Process Monitoring
Counterfactual Explanations for Predictive Business Process Monitoring
Tsung-Hao Huang
Andreas Metzger
Klaus Pohl
21
19
0
24 Feb 2022
XAI in the context of Predictive Process Monitoring: Too much to Reveal
XAI in the context of Predictive Process Monitoring: Too much to Reveal
Ghada Elkhawaga
Mervat Abuelkheir
M. Reichert
20
1
0
16 Feb 2022
Explainable Predictive Process Monitoring: A User Evaluation
Explainable Predictive Process Monitoring: A User Evaluation
Williams Rizzi
M. Comuzzi
Chiara Di Francescomarino
Chiara Ghidini
Suhwan Lee
F. Maggi
Alexander Nolte
FaML
XAI
22
8
0
15 Feb 2022
Local Post-Hoc Explanations for Predictive Process Monitoring in
  Manufacturing
Local Post-Hoc Explanations for Predictive Process Monitoring in Manufacturing
Nijat Mehdiyev
Peter Fettke
14
11
0
22 Sep 2020
On Large-Batch Training for Deep Learning: Generalization Gap and Sharp
  Minima
On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima
N. Keskar
Dheevatsa Mudigere
J. Nocedal
M. Smelyanskiy
P. T. P. Tang
ODL
308
2,890
0
15 Sep 2016
1