41 citations · 46 across the 3 of their papers we have counts for
5 papers
Can deep neural networks learn process model structure? An assessment framework and analysis
Jari Peeperkorn, Seppe vanden Broucke, Jochen De Weerdt
Predictive process monitoring concerns itself with the prediction of ongoing cases in (business) processes. Prediction tasks typically focus on remaining time, outcome, next event…
Creating Unbiased Public Benchmark Datasets with Data Leakage Prevention for Predictive Process Monitoring
Hans Weytjens, Jochen De Weerdt
Advances in AI, and especially machine learning, are increasingly drawing research interest and efforts towards predictive process monitoring, the subfield of process mining (PM) t…
Learning Uncertainty with Artificial Neural Networks for Improved Remaining Time Prediction of Business Processes
Hans Weytjens, Jochen De Weerdt
Artificial neural networks will always make a prediction, even when completely uncertain and regardless of the consequences. This obliviousness of uncertainty is a major obstacle t…
Process Model Forecasting Using Time Series Analysis of Event Sequence Data
Johannes De Smedt, Anton Yeshchenko, Artem Polyvyanyy +2
Process analytics is an umbrella of data-driven techniques which includes making predictions for individual process instances or overall process models. At the instance level, vari…
Process Outcome Prediction: CNN vs. LSTM (with Attention)
Hans Weytjens, Jochen De Weerdt
The early outcome prediction of ongoing or completed processes confers competitive advantage to organizations. The performance of classic machine learning and, more recently, deep…