| Quantifying Explainability in Outcome-Oriented Predictive Process Monitoring A Stevens, J De Smedt, J Peeperkorn | 24 | 2022 |
| Can deep neural networks learn process model structure? An assessment framework and analysis J Peeperkorn, S vanden Broucke, J De Weerdt Process Mining Workshops 433, 127-139, 2022 | 12 | 2022 |
| Assessing the robustness in predictive process monitoring through adversarial attacks A Stevens, J De Smedt, J Peeperkorn, J De Weerdt 2022 4th International Conference on Process Mining (ICPM), 56-63, 2022 | 6 | 2022 |
| Global conformance checking measures using shallow representation and deep learning J Peeperkorn, S vanden Broucke, J De Weerdt Engineering Applications of Artificial Intelligence 123, 106393, 2023 | 5 | 2023 |
| Can recurrent neural networks learn process model structure? J Peeperkorn, S vanden Broucke, J De Weerdt Journal of Intelligent Information Systems, 1-25, 2022 | 5 | 2022 |
| Conformance checking using activity and trace embeddings J Peeperkorn, S vanden Broucke, J De Weerdt International Conference on Business Process Management, 105-121, 2020 | 5 | 2020 |
| Enhancing Stochastic Petri Net-based Remaining Time Prediction using k-Nearest Neighbors J Vandenabeele, G Vermaut, J Peeperkorn, J De Weerdt ATAED @ Petri Nets 2022, 2022 | 3 | 2022 |
| Supervised Conformance Checking Using Recurrent Neural Network Classifiers J Peeperkorn, S vanden Broucke, J De Weerdt Process Mining Workshops. ICPM 2020. Lecture Notes in Business Information …, 2021 | 3 | 2021 |
| 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 | 1 | 2023 |
| Discovering high-quality process models despite data scarcity JN Adams, J Peeperkorn, T Brockhoff, I Terrier, H Göhner, MS Uysal, ... arXiv preprint arXiv:2310.11332, 2023 | 1 | 2023 |
| 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 | 1 | 2022 |
| Validation set sampling strategies for predictive process monitoring J Peeperkorn, S vanden Broucke, J De Weerdt Information Systems 121, 102330, 2024 | | 2024 |
| Vector Representation for Business Process: Graph Embedding for Domain Knowledge Integration TR Neubauer, J Peeperkorn, SM Peres, J De Weerdt, M Fantinato 2023 International Conference on Machine Learning and Applications (ICMLA …, 2023 | | 2023 |
| Novel Conformance Checking Methods and Validation Strategies for Deep Learning in Process Mining J Peeperkorn | | 2023 |
| Manifold learning in predictive process monitoring A Stevens, J Peeperkorn, J De Smedt, J De Weerdt Welcome to ORBEL 37, 153, 2023 | | 2023 |
| Forecasting geomagnetic storms using long short-term memory neural networks J Peeperkorn, R Dupuis, G Lapenta | | 2019 |
Jochen De WeerdtKU LeuvenVerified email at kuleuven.be
