When to intervene? Prescriptive Process Monitoring Under Uncertainty and Resource Constraints

15 June 2022

Papers citing "When to intervene? Prescriptive Process Monitoring Under Uncertainty and Resource Constraints"

15 / 15 papers shown

Title
Prescriptive Process Monitoring Under Resource Constraints: A Causal Inference Approach Mahmoud Shoush Marlon Dumas 41 22 0 07 Sep 2021
Prescriptive Process Monitoring for Cost-Aware Cycle Time Reduction Z. Bozorgi Irene Teinemaa Marlon Dumas M. Rosa Artem Polyvyanyy 38 35 0 15 May 2021
Learning Uncertainty with Artificial Neural Networks for Improved Remaining Time Prediction of Business Processes Hans Weytjens Jochen De Weerdt BDL 47 8 0 12 May 2021
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 353 1,935 0 12 Nov 2020
Process Mining Meets Causal Machine Learning: Discovering Causal Rules from Event Logs Z. Bozorgi Irene Teinemaa Marlon Dumas M. Rosa Artem Polyvyanyy CML AI4TS 36 45 0 03 Sep 2020
Prescriptive Business Process Monitoring for Recommending Next Best Actions Sven Weinzierl Sebastian Dunzer Sandra Zilker Martin Matzner 41 50 0 19 Aug 2020
Causality Learning: A New Perspective for Interpretable Machine Learning Guandong Xu Tri Dung Duong Q. Li S. Liu Xianzhi Wang XAI OOD CML 52 52 0 27 Jun 2020
Uncertainty in Gradient Boosting via Ensembles Aleksei Ustimenko Liudmila Prokhorenkova A. Malinin UQCV 76 95 0 18 Jun 2020
SGLB: Stochastic Gradient Langevin Boosting Aleksei Ustimenko Liudmila Prokhorenkova 67 19 0 20 Jan 2020
Aleatoric and Epistemic Uncertainty in Machine Learning: An Introduction to Concepts and Methods Eyke Hüllermeier Willem Waegeman PER UD 260 1,432 0 21 Oct 2019
Fire Now, Fire Later: Alarm-Based Systems for Prescriptive Process Monitoring Stephan A. Fahrenkrog-Petersen Niek Tax Irene Teinemaa Marlon Dumas M. Leoni F. Maggi Matthias Weidlich 33 43 0 23 May 2019
A Survey of Learning Causality with Data: Problems and Methods Ruocheng Guo Lu Cheng Jundong Li P. R. Hahn Huan Liu CML 63 168 0 25 Sep 2018
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 63 156 0 08 May 2018
Outcome-Oriented Predictive Process Monitoring: Review and Benchmark Irene Teinemaa Marlon Dumas M. Rosa F. Maggi 55 187 0 21 Jul 2017
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 894 9,364 0 06 Jun 2015