17 citations · 28 across the 9 of their papers we have counts for
9 papers
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…
Curation and Analysis of MIMICEL -- An Event Log for MIMIC-IV Emergency Department
Jia Wei, Chun Ouyang, Bemali Wickramanayake +3
The global issue of overcrowding in emergency departments (ED) necessitates the analysis of patient flow through ED to enhance efficiency and alleviate overcrowding. However, tradi…
TabAttackBench: A Benchmark for Adversarial Attacks on Tabular Data
Zhipeng He, Chun Ouyang, Lijie Wen +2
Adversarial attacks pose a significant threat to machine learning models by inducing incorrect predictions through imperceptible perturbations to input data. While these attacks ar…
Investigating Imperceptibility of Adversarial Attacks on Tabular Data: An Empirical Analysis
Zhipeng He, Chun Ouyang, Laith Alzubaidi +2
Adversarial attacks are a potential threat to machine learning models by causing incorrect predictions through imperceptible perturbations to the input data. While these attacks ha…
DALL-M: Context-Aware Clinical Data Augmentation with LLMs
Chihcheng Hsieh, Catarina Moreira, Isabel Blanco Nobre +5
X-ray images are vital in medical diagnostics, but their effectiveness is limited without clinical context. Radiologists often find chest X-rays insufficient for diagnosing underly…
Generating Feasible and Plausible Counterfactual Explanations for Outcome Prediction of Business Processes
Alexander Stevens, Chun Ouyang, Johannes De Smedt +1
In recent years, various machine and deep learning architectures have been successfully introduced to the field of predictive process analytics. Nevertheless, the inherent opacity…
MDF-Net for abnormality detection by fusing X-rays with clinical data
Chihcheng Hsieh, Isabel Blanco Nobre, Sandra Costa Sousa +5
This study investigates the effects of including patients' clinical information on the performance of deep learning (DL) classifiers for disease location in chest X-ray images. Alt…
AMORETTO: A Method for Deriving IoT-enriched Event Logs
Jia Wei, Chun Ouyang, Arthur H. M. ter Hofstede +1
Process analytics aims to gain insights into the behaviour and performance of business processes through the analysis of event logs, which record the execution of processes. With t…
Benchmarking Instance-Centric Counterfactual Algorithms for XAI: From White Box to Black Box
Catarina Moreira, Yu-Liang Chou, Chihcheng Hsieh +3
This study investigates the impact of machine learning models on the generation of counterfactual explanations by conducting a benchmark evaluation over three different types of mo…