3 papers
cs.LG2025
Crafting Imperceptible On-Manifold Adversarial Attacks for Tabular Data
Zhipeng He, Alexander Stevens, Chun Ouyang +3
Adversarial attacks on tabular data present unique challenges due to the heterogeneous nature of mixed categorical and numerical features. Unlike images where pixel perturbations m…
cs.LG2025
Leveraging Machine Learning and Enhanced Parallelism Detection for BPMN Model Generation from Text
Phuong Nam Lê, Charlotte Schneider-Depré, Alexandre Goossens +3
Efficient planning, resource management, and consistent operations often rely on converting textual process documents into formal Business Process Model and Notation (BPMN) models.…
cs.LG2024
Generating Realistic Adversarial Examples for Business Processes using Variational Autoencoders
Alexander Stevens, Jari Peeperkorn, Johannes De Smedt +1
In predictive process monitoring, predictive models are vulnerable to adversarial attacks, where input perturbations can lead to incorrect predictions. Unlike in computer vision, w…