Data mining methods for classification of Medium-Chain Acyl-CoA dehydrogenase deficiency (MCADD) using non-derivatized tandem MS neonatal screening data. - Tim Van den Bulcke; Paul Vanden Broucke; Viviane Van Hoof; Kristien Wouters; Seppe vanden Broucke; Geert Smits; Elke Smits; Sam Proesmans; Toon Van Genechten; François Eyskens (J. Biomed. Informatics, 2011)

On the Distinction between Truthful, Invisible, False and Unobserved Events An Event Existence Classification Framework and the Impact on Business Process Analytics Related Research Areas. - Filip Caron; Seppe K. L. M. vanden Broucke; Jan Vanthienen; Bart Baesens (AMCIS, 2012)

Improved Artificial Negative Event Generation to Enhance Process Event Logs. - Seppe K. L. M. vanden Broucke; Jochen De Weerdt; Bart Baesens; Jan Vanthienen (CAiSE, 2012)

Leveraging process discovery with trace clustering and text mining for intelligent analysis of incident management processes. - Jochen De Weerdt; Seppe K. L. M. vanden Broucke; Jan Vanthienen; Bart Baesens (IEEE Congress on Evolutionary Computation, 2012)

Validating and Enhancing Declarative Business Process Models Based on Allowed and Non-occurring Past Behavior. - Seppe K. L. M. vanden Broucke; Filip Caron; Jan Vanthienen; Bart Baesens (Business Process Management Workshops, 2013)

Uncovering the Relationship Between Event Log Characteristics and Process Discovery Techniques. - Seppe K. L. M. vanden Broucke; Cédric Delvaux; João Freitas; Taisiia Rogova; Jan Vanthienen; Bart Baesens (Business Process Management Workshops, 2013)

Volvo IT Belgium VINST. - Seppe vanden Broucke; Jan Vanthienen; Bart Baesens (BPIC@BPM, 2013)

An Exploratory Approach for Understanding Customer Behavior Processes Based on Clustering and Sequence Mining. - Alex Seret; Seppe K. L. M. vanden Broucke; Bart Baesens; Jan Vanthienen (Business Process Management Workshops, 2013)

A comprehensive benchmarking framework (CoBeFra) for conformance analysis between procedural process models and event logs in ProM. - Seppe K. L. M. vanden Broucke; Jochen De Weerdt; Jan Vanthienen; Bart Baesens (CIDM, 2013)

Active Trace Clustering for Improved Process Discovery. - Jochen De Weerdt; Seppe K. L. M. vanden Broucke; Jan Vanthienen; Bart Baesens (IEEE Trans. Knowl. Data Eng., 2013)

SECPI: Searching for Explanations for Clustered Process Instances. - Jochen De Weerdt; Seppe K. L. M. vanden Broucke (BPM, 2014)

Bidimensional Process Discovery for Mining BPMN Models. - Jochen De Weerdt; Seppe K. L. M. vanden Broucke; Filip Caron (Business Process Management Workshops, 2014)

Towards Location-Aware Process Modeling and Execution. - Xinwei Zhu; Guobin Zhu; Seppe K. L. M. vanden Broucke; Jan Vanthienen; Bart Baesens (Business Process Management Workshops, 2014)

Declarative process discovery with evolutionary computing. - Seppe K. L. M. vanden Broucke; Jan Vanthienen; Bart Baesens (IEEE Congress on Evolutionary Computation, 2014)

Perturbing event logs to identify cost reduction opportunities: A genetic algorithm-based approach. - Wei Zhe Low; Jochen De Weerdt; Moe Thandar Wynn; Arthur H. M. ter Hofstede; Wil M. P. van der Aalst; Seppe K. L. M. vanden Broucke (IEEE Congress on Evolutionary Computation, 2014)

On Merging Business Process Management and Geographic Information Systems: Modeling and Execution of Ecological Concerns in Processes. - Xinwei Zhu; Guobin Zhu; Seppe vanden Broucke; Jan Recker (GRMSE, 2014)

Event-Based Real-Time Decomposed Conformance Analysis. - Seppe K. L. M. vanden Broucke; Jorge Munoz-Gama; Josep Carmona 001; Bart Baesens; Jan Vanthienen (OTM Conferences, 2014)

A dynamic understanding of customer behavior processes based on clustering and sequence mining. - Alex Seret; Seppe K. L. M. vanden Broucke; Bart Baesens; Jan Vanthienen (Expert Syst. Appl., 2014)

Determining Process Model Precision and Generalization with Weighted Artificial Negative Events. - Seppe K. L. M. vanden Broucke; Jochen De Weerdt; Jan Vanthienen; Bart Baesens (IEEE Trans. Knowl. Data Eng., 2014)

Advances in Process Mining: Artificial negative events and othertechniques. - Seppe vanden Broucke (2014)

Incorporating Negative Information in Process Discovery. - Hernán Ponce de León; Josep Carmona 001; Seppe K. L. M. vanden Broucke (BPM, 2015)

Profit maximizing logistic regression modeling for customer churn prediction. - Eugen Stripling; Seppe vanden Broucke; Katrien Antonio; Bart Baesens; Monique Snoeck (DSAA, 2015)

Decision Mining in a Broader Context: An Overview of the Current Landscape and Future Directions. - Johannes De Smedt; Seppe K. L. M. vanden Broucke; Josué Obregon; Aekyung Kim; Jae-Yoon Jung 001; Jan Vanthienen (Business Process Management Workshops, 2016)

A guide for the application of analytics on healthcare processes: A dynamic view on patient pathways. - Jasmien Lismont; Anne-Sophie Janssens; Irina Odnoletkova; Seppe vanden Broucke; Filip Caron; Jan Vanthienen (Comput. Biol. Medicine, 2016)

Revising history for cost-informed process improvement. - Wei Zhe Low; Seppe K. L. M. vanden Broucke; Moe Thandar Wynn; Arthur H. M. ter Hofstede; Jochen De Weerdt; Wil M. P. van der Aalst (Computing, 2016)

Enabling flexible location-aware business process modeling and execution. - Xinwei Zhu; Seppe vanden Broucke; Guobin Zhu; Jan Vanthienen; Bart Baesens (Decis. Support Syst., 2016)

On the gap between reality and registration: a business event analysis classification framework. - Seppe K. L. M. vanden Broucke; Filip Caron; Jasmien Lismont; Jan Vanthienen; Bart Baesens (Inf. Technol. Manag., 2016)

Towards a Holistic Discovery of Decisions in Process-Aware Information Systems. - Johannes De Smedt; Faruk Hasic; Seppe K. L. M. vanden Broucke; Jan Vanthienen (BPM, 2017)

An Approach for Incorporating Expert Knowledge in Trace Clustering. - Pieter De Koninck; Klaas Nelissen; Bart Baesens; Seppe vanden Broucke; Monique Snoeck; Jochen De Weerdt (CAiSE, 2017)

Improving Resampling-based Ensemble in Churn Prediction. - Bing Zhu 005; Seppe vanden Broucke; Bart Baesens; Sebastián Maldonado (LIDTA@PKDD/ECML, 2017)

Explaining clusterings of process instances. - Pieter De Koninck; Jochen De Weerdt; Seppe K. L. M. vanden Broucke (Data Min. Knowl. Discov., 2017)

Fodina: A robust and flexible heuristic process discovery technique. - Seppe K. L. M. vanden Broucke; Jochen De Weerdt (Decis. Support Syst., 2017)

An empirical comparison of techniques for the class imbalance problem in churn prediction. - Bing Zhu 005; Bart Baesens; Seppe K. L. M. vanden Broucke (Inf. Sci., 2017)

act2vec, trace2vec, log2vec, and model2vec: Representation Learning for Business Processes. - Pieter De Koninck; Seppe vanden Broucke; Jochen De Weerdt (BPM, 2018)

Profit Maximizing Logistic Regression Modeling for Credit Scoring. - Arnout Devos; Jakob Dhondt; Eugen Stripling; Bart Baesens; Seppe vanden Broucke; Gaurav S. Sukhatme (DSW, 2018)

An Interview with Bart Baesens, One of the Authors of Principles of Database Management. - Wilfried Lemahieu; Seppe vanden Broucke; Bart Baesens (Big Data, 2018)

Isolation-based conditional anomaly detection on mixed-attribute data to uncover workers' compensation fraud. - Eugen Stripling; Bart Baesens; Barak Chizi; Seppe vanden Broucke (Decis. Support Syst., 2018)

Incorporating negative information to process discovery of complex systems. - Hernán Ponce de León; Lucio Nardelli; Josep Carmona 001; Seppe K. L. M. vanden Broucke (Inf. Sci., 2018)

Benchmarking sampling techniques for imbalance learning in churn prediction. - Bing Zhu 005; Bart Baesens; Aimée Backiel; Seppe K. L. M. vanden Broucke (J. Oper. Res. Soc., 2018)

Profit maximizing logistic model for customer churn prediction using genetic algorithms. - Eugen Stripling; Seppe vanden Broucke; Katrien Antonio; Bart Baesens; Monique Snoeck (Swarm Evol. Comput., 2018)

Swipe and Tell: Using Implicit Feedback to Predict User Engagement on Tablets. - Klaas Nelissen; Monique Snoeck; Seppe K. L. M. vanden Broucke; Bart Baesens (ACM Trans. Inf. Syst., 2018)

Predictive Process Monitoring in Operational Logistics: A Case Study in Aviation. - Björn Rafn Gunnarsson; Seppe K. L. M. vanden Broucke; Jochen De Weerdt (Business Process Management Workshops, 2019)

Optimizing Marketing Campaign Targeting Using Uncertainty-Based Predictive Modelling. - Björn Rafn Gunnarsson; Seppe vanden Broucke; Jochen De Weerdt (ICDM Workshops, 2019)

Closing the Gap Between Experts and Novices Using Analytics-as-a-Service: An Experimental Study. - Jasmien Lismont; Tine Van Calster; María Óskarsdóttir; Seppe vanden Broucke; Bart Baesens; Wilfried Lemahieu; Jan Vanthienen (Bus. Inf. Syst. Eng., 2019)

Holistic discovery of decision models from process execution data. - Johannes De Smedt; Faruk Hasic; Seppe K. L. M. vanden Broucke; Jan Vanthienen (Knowl. Based Syst., 2019)

IRIC: An R library for binary imbalanced classification. - Bing Zhu 005; Zihan Gao; Junkai Zhao; Seppe K. L. M. vanden Broucke (SoftwareX, 2019)

Conformance Checking Using Activity and Trace Embeddings. - Jari Peeperkorn; Seppe vanden Broucke; Jochen De Weerdt (BPM (Forum), 2020)

Supervised Conformance Checking Using Recurrent Neural Network Classifiers. - Jari Peeperkorn; Seppe vanden Broucke; Jochen De Weerdt (ICPM Workshops, 2020)

Predicting student success in a blended learning environment. - Steven Van Goidsenhoven; Daria Bogdanova; Galina Deeva; Seppe vanden Broucke; Jochen De Weerdt; Monique Snoeck (LAK, 2020)

A Comparative Study of Representation Learning Techniques for Dynamic Networks. - Carlos Ortega Vázquez; Sandra Mitrovic; Jochen De Weerdt; Seppe vanden Broucke (WorldCIST (3), 2020)

An Experimental Investigation of Calibration Techniques for Imbalanced Data. - Lanlan Huang; Junkai Zhao; Bing Zhu 005; Hao Chen 088; Seppe K. L. M. vanden Broucke (IEEE Access, 2020)

Profit driven decision trees for churn prediction. - Sebastiaan Höppner; Eugen Stripling; Bart Baesens; Seppe vanden Broucke; Tim Verdonck (Eur. J. Oper. Res., 2020)

Can Deep Neural Networks Learn Process Model Structure? An Assessment Framework and Analysis. - Jari Peeperkorn; Seppe vanden Broucke; Jochen De Weerdt (ICPM Workshops, 2021)

Exploring Automated GDPR-Compliance in Requirements Engineering: A Systematic Mapping Study. - Abdel-Jaouad Aberkane; Geert Poels; Seppe vanden Broucke (IEEE Access, 2021)

Deep learning for credit scoring: Do or don't? - Björn Rafn Gunnarsson; Seppe vanden Broucke; Bart Baesens; María Óskarsdóttir; Wilfried Lemahieu (Eur. J. Oper. Res., 2021)

Expert-driven trace clustering with instance-level constraints. - Pieter De Koninck; Klaas Nelissen; Seppe vanden Broucke; Bart Baesens; Monique Snoeck; Jochen De Weerdt (Knowl. Inf. Syst., 2021)

Optimization framework for DFG-based automated process discovery approaches. - Adriano Augusto; Marlon Dumas; Marcello La Rosa; Sander J. J. Leemans; Seppe K. L. M. vanden Broucke (Softw. Syst. Model., 2021)

Outcome-Oriented Predictive Process Monitoring on Positive and Unlabelled Event Logs. - Jari Peeperkorn; Carlos Ortega Vázquez; Alexander Stevens; Johannes De Smedt; Seppe vanden Broucke; Jochen De Weerdt (ICPM Workshops, 2022)

A framework for encoding the multi-location load state of a business process. - Björn Rafn Gunnarsson; Jochen De Weerdt; Seppe vanden Broucke (PMAI@IJCAI, 2022)

The Hidden Cost of Fraud: An Instance-Dependent Cost-Sensitive Approach for Positive and Unlabeled Learning. - Carlos Ortega Vázquez; Jochen De Weerdt; Seppe vanden Broucke (LIDTA, 2022)

Predicting the State of a House Using Google Street View - An Analysis of Deep Binary Classification Models for the Assessment of the Quality of Flemish Houses. - Margot Geerts; Kiran Shaikh; Jochen De Weerdt; Seppe vanden Broucke (RCIS, 2022)

Investigating Organizational Factors Associated with GDPR Noncompliance using Privacy Policies: A Machine Learning Approach. - Abdel-Jaouad Aberkane; Seppe vanden Broucke; Geert Poels (TPS-ISA, 2022)

A GAN-based hybrid sampling method for imbalanced customer classification. - Bing Zhu 005; Xin Pan; Seppe vanden Broucke; Jin Xiao (Inf. Sci., 2022)

Decision as a Service (DaaS): A Service-Oriented Architecture Approach for Decisions in Processes. - Faruk Hasic; Johannes De Smedt; Seppe vanden Broucke; Estefanía Serral (IEEE Trans. Serv. Comput., 2022)

DyLoPro: Profiling the Dynamics of Event Logs. - Brecht Wuyts; Hans Weytjens; Seppe vanden Broucke; Jochen De Weerdt (BPM, 2023)

Discovering high-quality process models despite data scarcity. - Jan Niklas Adams; Jari Peeperkorn; Tobias Brockhoff; Isabelle Terrier; Heiko Göhner; Merih Seran Uysal; Seppe vanden Broucke; Jochen De Weerdt; Wil M. P. van der Aalst (ER (Companion), 2023)

An Evolutionary Geospatial Regression Tree. - Margot Geerts; Seppe vanden Broucke; Jochen De Weerdt (STRL@IJCAI, 2023)

Geospatial Prediction Using Road Topology: A Graph-based Perspective. - Yameng Guo; Seppe vanden Broucke (STRL@IJCAI, 2023)

Toward Data Protection by Design: Assessing the Current State of GDPR Disclosure in Web Applications. - Abdel-Jaouad Aberkane; Seppe vanden Broucke; Geert Poels (REW, 2023)

Global conformance checking measures using shallow representation and deep learning. - Jari Peeperkorn; Seppe vanden Broucke; Jochen De Weerdt (Eng. Appl. Artif. Intell., 2023)

A Survey of Methods and Input Data Types for House Price Prediction. - Margot Geerts; Seppe vanden Broucke; Jochen De Weerdt (ISPRS Int. J. Geo Inf., 2023)

A Direct Data Aware LSTM Neural Network Architecture for Complete Remaining Trace and Runtime Prediction. - Björn Rafn Gunnarsson; Seppe vanden Broucke; Jochen De Weerdt (IEEE Trans. Serv. Comput., 2023)

A two-step anomaly detection based method for PU classification in imbalanced data sets. - Carlos Ortega Vázquez; Seppe vanden Broucke; Jochen De Weerdt (Data Min. Knowl. Discov., 2023)

Regularization oversampling for classification tasks: To exploit what you do not know. - Lennert Van der Schraelen; Kristof Stouthuysen; Seppe K. L. M. vanden Broucke; Tim Verdonck (Inf. Sci., 2023)

Can recurrent neural networks learn process model structure? - Jari Peeperkorn; Seppe vanden Broucke; Jochen De Weerdt (J. Intell. Inf. Syst., 2023)

A bagging-based selective ensemble model for churn prediction on imbalanced data. - Bing Zhu 005; Cheng Qian; Seppe vanden Broucke; Jin Xiao; Yuanyuan Li (Expert Syst. Appl., 2023)

Understanding Organizational Transitions: Interpretable Top Manager Turnover Prediction using a Heterogeneous Graph Neural Network. - Yameng Guo; Qiuzhen Ren; Seppe vanden Broucke (CSAI, 2024)

A Critique on Transductive Evaluation for GNN Node Classification. - Yameng Guo; Seppe vanden Broucke (DataMod, 2024)

Learning from Uncertainty: Improving Churn Prediction using Conformal Confidence Intervals. - Yameng Guo; Seppe vanden Broucke (ICMLA, 2024)

SuTraN: an Encoder-Decoder Transformer for Full-Context-Aware Suffix Prediction of Business Processes. - Brecht Wuyts; Seppe K. L. M. vanden Broucke; Jochen De Weerdt (ICPM, 2024)

CaLenDiR: Mitigating Case-Length Distortion in Deep-Learning-Based Predictive Process Monitoring. - Brecht Wuyts; Seppe K. L. M. vanden Broucke; Jochen De Weerdt (ICPM Workshops, 2024)

Leveraging ChatGPT for GDPR Compliance in Requirements Engineering: A Pilot Study. - Abdel-Jaouad Aberkane; Seppe vanden Broucke; Geert Poels; Georgios Georgiadis (SpaCCS, 2024)

A Spatial Loss Function for Gradient Boosted Trees. - Margot Geerts; Seppe vanden Broucke; Jochen De Weerdt (STRL@IJCAI, 2024)

Explainable Deep Learning to Classify Royal Navy Ships. - Bart Baesens; Amy Adams; Rodrigo Pacheco-Ruiz; Ann-Sophie Baesens; Seppe K. L. M. vanden Broucke (IEEE Access, 2024)

Evaluating text classification: A benchmark study. - Manon Reusens; Alexander Stevens; Jonathan Tonglet; Johannes De Smedt; Wouter Verbeke; Seppe vanden Broucke; Bart Baesens (Expert Syst. Appl., 2024)

LS-ICE: A Load State Intercase Encoding framework for improved predictive monitoring of business processes. - Björn Rafn Gunnarsson; Seppe vanden Broucke; Jochen De Weerdt (Inf. Syst., 2024)

Validation set sampling strategies for predictive process monitoring. - Jari Peeperkorn; Seppe vanden Broucke; Jochen De Weerdt (Inf. Syst., 2024)

Hellinger distance decision trees for PU learning in imbalanced data sets. - Carlos Ortega Vázquez; Seppe vanden Broucke; Jochen De Weerdt (Mach. Learn., 2024)

Special issue on feature engineering editorial. - Tim Verdonck; Bart Baesens; María Óskarsdóttir; Seppe vanden Broucke (Mach. Learn., 2024)

Enhancing geospatial prediction models with feature engineering from road networks: a graph-driven approach. - Yameng Guo; Seppe vanden Broucke (Int. J. Geogr. Inf. Sci., 2024)

GeoRF: a geospatial random forest. - Margot Geerts; Seppe vanden Broucke; Jochen De Weerdt (Data Min. Knowl. Discov., 2024)

On the Performance of LLMs for Real Estate Appraisal. - Margot Geerts; Manon Reusens; Bart Baesens; Seppe vanden Broucke; Jochen De Weerdt (CoRR, 2025)