research
∙
06/07/2023
Timing Process Interventions with Causal Inference and Reinforcement Learning
The shift from the understanding and prediction of processes to their op...
share
research
∙
12/13/2022
Can recurrent neural networks learn process model structure?
Various methods using machine and deep learning have been proposed to ta...
research
∙
08/16/2022
Predicting student performance using sequence classification with time-based windows
A growing number of universities worldwide use various forms of online a...
research
∙
06/27/2022
Enhancing Stochastic Petri Net-based Remaining Time Prediction using k-Nearest Neighbors
Reliable remaining time prediction of ongoing business processes is a hi...
research
∙
06/13/2022
Learning Uncertainty with Artificial Neural Networks for Improved Predictive Process Monitoring
The inability of artificial neural networks to assess the uncertainty of...
research
∙
02/24/2022
Can deep neural networks learn process model structure? An assessment framework and analysis
Predictive process monitoring concerns itself with the prediction of ong...
research
∙
10/13/2021
Expert-driven Trace Clustering with Instance-level Constraints
Within the field of process mining, several different trace clustering a...
research
∙
07/05/2021
Creating Unbiased Public Benchmark Datasets with Data Leakage Prevention for Predictive Process Monitoring
Advances in AI, and especially machine learning, are increasingly drawin...
research
∙
05/12/2021
Learning Uncertainty with Artificial Neural Networks for Improved Remaining Time Prediction of Business Processes
Artificial neural networks will always make a prediction, even when comp...
research
∙
05/03/2021
Process Model Forecasting Using Time Series Analysis of Event Sequence Data
Process analytics is an umbrella of data-driven techniques which include...
research
∙
04/14/2021
Process Outcome Prediction: CNN vs. LSTM (with Attention)
The early outcome prediction of ongoing or completed processes confers c...
research
∙
11/05/2020
