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Alexander Paul Stevens
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Explainability and fairness in machine learning: Improve fair end-to-end lending for kiva
A Stevens, P Deruyck, Z Van Veldhoven, J Vanthienen
2020 IEEE Symposium Series on Computational Intelligence (SSCI), 1241-1248, 2020
252020
Quantifying Explainability in Outcome-Oriented Predictive Process Monitoring
A Stevens, J De Smedt, J Peeperkorn
242022
Explainability in process outcome prediction: Guidelines to obtain interpretable and faithful models
A Stevens, J De Smedt
European Journal of Operational Research, 2023
14*2023
Assessing the Robustness in Predictive Process Monitoring through Adversarial Attacks
A Stevens, J De Smedt, J Peeperkorn, J De Weerdt
International Conference on Process Mining (ICPM), 2022
62022
Manifold Learning for Adversarial Robustness in Predictive Process Monitoring
A Stevens, J Peeperkorn, J De Smedt, J De Weerdt
2023 5th International Conference on Process Mining (ICPM), 17-24, 2023
12023
Outcome-Oriented Predictive Process Monitoring on Positive and Unlabelled Event Logs
J Peeperkorn, C Ortega Vázquez, A Stevens, J De Smedt, ...
International Conference on Process Mining, 255-268, 2022
12022
Generating Feasible and Plausible Counterfactual Explanations for Outcome Prediction of Business Processes
A Stevens, C Ouyang, J De Smedt, C Moreira
arXiv preprint arXiv:2403.09232, 2024
2024
Manifold learning in predictive process monitoring
A Stevens, J Peeperkorn, J De Smedt, J De Weerdt
Welcome to ORBEL 37, 153, 2023
2023
A review and experimental evaluation of the state-of-the-art in text classification
M Reusens, A Stevens, J Tonglet, J De Smedt, W Verbeke, ...
Welcome to ORBEL 37, 131, 2023
2023
2023 5 th International Conference on Process Mining ICPM 2023
M Dumas, O López-Pintado, F Meneghello, C Di Francescomarino, ...
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