A Critical Evaluation Study of Model-Log Metrics in Process Discovery. - Jochen De Weerdt; Manu De Backer; Jan Vanthienen; Bart Baesens (Business Process Management Workshops, 2010)

Advanced Care-Flow Mining and Analysis. - Filip Caron; Jan Vanthienen; Jochen De Weerdt; Bart Baesens (Business Process Management Workshops (1), 2011)

A robust F-measure for evaluating discovered process models. - Jochen De Weerdt; Manu De Backer; Jan Vanthienen; Bart Baesens (CIDM, 2011)

Process discovery in event logs: An application in the telecom industry. - Stijn Goedertier; Jochen De Weerdt; David Martens; Jan Vanthienen; Bart Baesens (Appl. Soft Comput., 2011)

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)

Getting a Grasp on Clinical Pathway Data: An Approach Based on Process Mining. - Jochen De Weerdt; Filip Caron; Jan Vanthienen; Bart Baesens (PAKDD Workshops, 2012)

A multi-dimensional quality assessment of state-of-the-art process discovery algorithms using real-life event logs. - Jochen De Weerdt; Manu De Backer; Jan Vanthienen; Bart Baesens (Inf. Syst., 2012)

Business process discovery: new techniques and applications. - Jochen De Weerdt (2012)

Cost-Aware Business Process Management: A Research Agenda. - Moe Wynn; Jochen De Weerdt; Arthur H. M. ter Hofstede; Wil M. P. van der Aalst; Hajo A. Reijers; Michael Adams 001; Chun Ouyang 001; Michael Rosemann; Wei Zhe Low (ACIS, 2013)

Report: Business Process Intelligence Challenge 2013. - Boudewijn F. van Dongen; Barbara Weber; Diogo R. Ferreira; Jochen De Weerdt (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)

Process Mining for the multi-faceted analysis of business processes - A case study in a financial services organization. - Jochen De Weerdt; Annelies Schupp; An Vanderloock; Bart Baesens (Comput. Ind., 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)

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)

Multi-paradigm Process Mining: Retrieving Better Models by Combining Rules and Sequences - (Short Paper). - Johannes De Smedt; Jochen De Weerdt; Jan Vanthienen (OTM Conferences, 2014)

Monitoring care processes in the gynecologic oncology department. - Filip Caron; Jan Vanthienen; Kris Vanhaecht; Erik van Limbergen; Jochen De Weerdt; Bart Baesens (Comput. Biol. Medicine, 2014)

Process mining analysis of conceptual modeling behavior of novices - empirical study using JMermaid modeling and experimental logging environment. - Gayane Sedrakyan; Monique Snoeck; Jochen De Weerdt (Comput. Hum. Behav., 2014)

Controlled automated discovery of collections of business process models. - Luciano García-Bañuelos; Marlon Dumas; Marcello La Rosa; Jochen De Weerdt; Chathura C. Ekanayake (Inf. Syst., 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)

Gamification of Declarative Process Models for Learning and Model Verification. - Johannes De Smedt; Jochen De Weerdt; Estefanía Serral; Jan Vanthienen (Business Process Management Workshops, 2015)

Fusion Miner: Process discovery for mixed-paradigm models. - Johannes De Smedt; Jochen De Weerdt; Jan Vanthienen (Decis. Support Syst., 2015)

Determining the Number of Trace Clusters: a Stability-based Approach. - Pieter De Koninck; Jochen De Weerdt (ATAED@Petri Nets/ACSD, 2016)

A Stability Assessment Framework for Process Discovery Techniques. - Pieter De Koninck; Jochen De Weerdt (BPM, 2016)

Multi-objective Trace Clustering: Finding More Balanced Solutions. - Pieter De Koninck; Jochen De Weerdt (Business Process Management Workshops, 2016)

Improving Understandability of Declarative Process Models by Revealing Hidden Dependencies. - Johannes De Smedt; Jochen De Weerdt; Estefanía Serral; Jan Vanthienen (CAiSE, 2016)

Automating immediate and personalized feedback taking conceptual modelling education to a next level. - Estefanía Serral; Jochen De Weerdt; Gayane Sedrakyan; Monique Snoeck (RCIS, 2016)

Mixed-Paradigm Process Modeling with Intertwined State Spaces. - Johannes De Smedt; Jochen De Weerdt; Jan Vanthienen; Geert Poels (Bus. Inf. Syst. Eng., 2016)

Erratum to: Mixed-Paradigm Process Modeling with Intertwined State Spaces. - Johannes De Smedt; Jochen De Weerdt; Jan Vanthienen; Geert Poels (Bus. Inf. Syst. Eng., 2016)

Process-mining enabled feedback: "Tell me what I did wrong" vs. "tell me how to do it right". - Gayane Sedrakyan; Jochen De Weerdt; Monique Snoeck (Comput. Hum. Behav., 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)

Dropout Prediction in MOOCs: A Comparison Between Process and Sequence Mining. - Galina Deeva; Johannes De Smedt; Pieter De Koninck; Jochen De Weerdt (Business Process Management Workshops, 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)

Scalable RFM-enriched Representation Learning for Churn Prediction. - Sandra Mitrovic; Gaurav Singh 001; Bart Baesens; Wilfried Lemahieu; Jochen De Weerdt (DSAA, 2017)

Churn Prediction Using Dynamic RFM-Augmented Node2vec. - Sandra Mitrovic; Bart Baesens; Wilfried Lemahieu; Jochen De Weerdt (PAP@PKDD/ECML, 2017)

Behavioral Constraint Template-Based Sequence Classification. - Johannes De Smedt; Galina Deeva; Jochen De Weerdt (ECML/PKDD (2), 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)

Change visualisation: Analysing the resource and timing differences between two event logs. - Wei Zhe Low; Wil M. P. van der Aalst; Arthur H. M. ter Hofstede; Moe Thandar Wynn; Jochen De Weerdt (Inf. Syst., 2017)

Similarity-Based Approaches for Determining the Number of Trace Clusters in Process Discovery. - Pieter De Koninck; Jochen De Weerdt (Trans. Petri Nets Other Model. Concurr., 2017)

Combining Temporal Aspects of Dynamic Networks with Node2Vec for a more Efficient Dynamic Link Prediction. - Sam De Winter; Tim Decuypere; Sandra Mitrovic; Bart Baesens; Jochen De Weerdt (ASONAM, 2018)

Understanding Automated Feedback in Learning Processes by Mining Local Patterns. - Galina Deeva; Jochen De Weerdt (Business Process Management Workshops, 2018)

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

Discovering the Impact of Students' Modeling Behavior on their Final Performance. - Galina Deeva; Monique Snoeck; Jochen De Weerdt (PoEM, 2018)

On the operational efficiency of different feature types for telco Churn prediction. - Sandra Mitrovic; Bart Baesens; Wilfried Lemahieu; Jochen De Weerdt (Eur. J. Oper. Res., 2018)

Discovering hidden dependencies in constraint-based declarative process models for improving understandability. - Johannes De Smedt; Jochen De Weerdt; Estefanía Serral; Jan Vanthienen (Inf. Syst., 2018)

A comparison of methods for link sign prediction with signed network embeddings. - Sandra Mitrovic; Laurent Lecoutere; Jochen De Weerdt (ASONAM, 2019)

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)

Mining Behavioural Patterns in Urban Mobility Sequences Using Foursquare Check-in Data from Tokyo. - Galina Deeva; Johannes De Smedt; Jochen De Weerdt; María Óskarsdóttir (COMPLEX NETWORKS (2), 2019)

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

Scalable Mixed-Paradigm Trace Clustering using Super-Instances. - Pieter De Koninck; Jochen De Weerdt (ICPM, 2019)

Representation Learning in Graphs for Credit Card Fraud Detection. - Rafaël Van Belle; Sandra Mitrovic; Jochen De Weerdt (MIDAS@PKDD, 2019)

A Comparative Study of Community Detection Techniques for Large Evolving Graphs. - Lauranne Coppens; Jonathan De Venter; Sandra Mitrovic; Jochen De Weerdt (PKDD/ECML Workshops (1), 2019)

Trace Clustering. - Jochen De Weerdt (Encyclopedia of Big Data Technologies, 2019)

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

Process Outcome Prediction: CNN vs. LSTM (with Attention). - Hans Weytjens; Jochen De Weerdt (Business Process Management Workshops, 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)

Recommendations for enhancing the usability and understandability of process mining in healthcare. - Niels Martin; Jochen De Weerdt; Carlos Fernández-Llatas; Avigdor Gal; Roberto Gatta; Gema Ibáñez; Owen A. Johnson; Felix Mannhardt; Luis Marco-Ruiz; Steven Mertens; Jorge Munoz-Gama; Fernando Seoane; et al. (Artif. Intell. Medicine, 2020)

Predictive Process Model Monitoring using Recurrent Neural Networks. - Johannes De Smedt; Jochen De Weerdt; Junichiro Mori; Masanao Ochi (CoRR, 2020)

Churn modeling with probabilistic meta paths-based representation learning. - Sandra Mitrovic; Jochen De Weerdt (Inf. Process. Manag., 2020)

Mining Behavioral Sequence Constraints for Classification. - Johannes De Smedt; Galina Deeva; Jochen De Weerdt (IEEE Trans. Knowl. Data Eng., 2020)

Learning Uncertainty with Artificial Neural Networks for Improved Remaining Time Prediction of Business Processes. - Hans Weytjens; Jochen De Weerdt (BPM, 2021)

Creating Unbiased Public Benchmark Datasets with Data Leakage Prevention for Predictive Process Monitoring. - Hans Weytjens; Jochen De Weerdt (Business Process Management Workshops, 2021)

Supporting Data-Aware Processes with MERODE. - Monique Snoeck; Johannes De Smedt; Jochen De Weerdt (BPMDS/EMMSAD@CAiSE, 2021)

Process Model Forecasting Using Time Series Analysis of Event Sequence Data. - Johannes De Smedt; Anton Yeshchenko; Artem Polyvyanyy; Jochen De Weerdt; Jan Mendling (ER, 2021)

Neural Machine Translation for Conditional Generation of Novel Procedures. - Joppe Geluykens; Sandra Mitrovic; Carlos Ortega Vázquez; Teodoro Laino; Alain C. Vaucher; Jochen De Weerdt (HICSS, 2021)

A Bridging Model for Process Mining and IoT. - Yannis Bertrand; Jochen De Weerdt; Estefanía Serral (ICPM Workshops, 2021)

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

A review of automated feedback systems for learners: Classification framework, challenges and opportunities. - Galina Deeva; Daria Bogdanova; Estefanía Serral; Monique Snoeck; Jochen De Weerdt (Comput. Educ., 2021)

Special issue on business process intelligence. - Andrea Burattin; Jochen De Weerdt; Boudewijn F. van Dongen; Jan Claes; Wil M. P. van der Aalst (Computing, 2021)

Conformance Checking in Process Mining. - Mieke Jans; Jochen De Weerdt; Benoît Depaire; Marlon Dumas; Gert Janssenswillen (Inf. Syst., 2021)

tcc2vec: RFM-informed representation learning on call graphs for churn prediction. - Sandra Mitrovic; Bart Baesens; Wilfried Lemahieu; Jochen De Weerdt (Inf. Sci., 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)

Foundations of Process Event Data. - Jochen De Weerdt; Moe Thandar Wynn (Process Mining Handbook, 2022)

Enhancing Stochastic Petri Net-based Remaining Time Prediction using k-Nearest Neighbors. - Jarne Vandenabeele; Gilles Vermaut; Jari Peeperkorn; Jochen De Weerdt (ATAED@Petri Nets, 2022)

Evaluation of Joint Modeling Techniques for Node Embedding and Community Detection on Graphs. - Simon Hiel; Lore Nicolaers; Carlos Ortega Vázquez; Sandra Mitrovic; Bart Baesens; Jochen De Weerdt (ASONAM, 2022)

Assessing the Suitability of Traditional Event Log Standards for IoT-Enhanced Event Logs. - Yannis Bertrand; Jochen De Weerdt; Estefanía Serral (Business Process Management Workshops, 2022)

Defining Data Quality Issues in Process Mining with IoT Data. - Yannis Bertrand; Rafaël Van Belle; Jochen De Weerdt; Estefanía Serral (ICPM Workshops, 2022)

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)

Assessing the Robustness in Predictive Process Monitoring through Adversarial Attacks. - Alexander Stevens; Johannes De Smedt; Jari Peeperkorn; Jochen De Weerdt (ICPM, 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)

Learning uncertainty with artificial neural networks for predictive process monitoring. - Hans Weytjens; Jochen De Weerdt (Appl. Soft Comput., 2022)

Learning Uncertainty with Artificial Neural Networks for Improved Predictive Process Monitoring. - Hans Weytjens; Jochen De Weerdt (CoRR, 2022)

Inductive Graph Representation Learning for fraud detection. - Rafaël Van Belle; Charles Van Damme; Hendrik Tytgat; Jochen De Weerdt (Expert Syst. Appl., 2022)

Predicting student performance using sequence classification with time-based windows. - Galina Deeva; Johannes De Smedt; Cecilia Saint-Pierre; Richard Weber; Jochen De Weerdt (Expert Syst. Appl., 2022)

Educational Sequence Mining for Dropout Prediction in MOOCs: Model Building, Evaluation, and Benchmarking. - Galina Deeva; Johannes De Smedt; Jochen De Weerdt (IEEE Trans. Learn. Technol., 2022)

A Novel Multi-perspective Trace Clustering Technique for IoT-Enhanced Processes: A Case Study in Smart Manufacturing. - Yannis Bertrand; Jochen De Weerdt; Estefanía Serral (BPM, 2023)

Timed Process Interventions: Causal Inference vs. Reinforcement Learning. - Hans Weytjens; Wouter Verbeke; Jochen De Weerdt (Business Process Management Workshops, 2023)

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

CORE: A Few-Shot Company Relation Classification Dataset for Robust Domain Adaptation. - Philipp Borchert; Jochen De Weerdt; Kristof Coussement; Arno De Caigny; Marie-Francine Moens (EMNLP, 2023)

Investigating Bias in Multilingual Language Models: Cross-Lingual Transfer of Debiasing Techniques. - Manon Reusens; Philipp Borchert; Margot Mieskes; Jochen De Weerdt; Bart Baesens (EMNLP, 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)

Vector Representation for Business Process: Graph Embedding for Domain Knowledge Integration. - Thais Rodrigues Neubauer; Jari Peeperkorn; Sarajane Marques Peres; Jochen De Weerdt; Marcelo Fantinato (ICMLA, 2023)

Manifold Learning for Adversarial Robustness in Predictive Process Monitoring. - Alexander Stevens; Jari Peeperkorn; Johannes De Smedt; Jochen De Weerdt (ICPM, 2023)

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

Timing Process Interventions with Causal Inference and Reinforcement Learning. - Hans Weytjens; Wouter Verbeke; Jochen De Weerdt (CoRR, 2023)

CATCHM: A novel network-based credit card fraud detection method using node representation learning. - Rafaël Van Belle; Bart Baesens; Jochen De Weerdt (Decis. Support Syst., 2023)

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

Extending business failure prediction models with textual website content using deep learning. - Philipp Borchert; Kristof Coussement; Arno De Caigny; Jochen De Weerdt (Eur. J. Oper. Res., 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)

Process model forecasting and change exploration using time series analysis of event sequence data. - Johannes De Smedt; Anton Yeshchenko; Artem Polyvyanyy; Jochen De Weerdt; Jan Mendling (Data Knowl. Eng., 2023)

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

Process-Data Quality: The True Frontier of Process Mining. - Arthur H. M. ter Hofstede; Agnes Koschmider; Andrea Marrella; Robert Andrews 001; Dominik Andreas Fischer; Sareh Sadeghianasl; Moe Thandar Wynn; Marco Comuzzi; Jochen De Weerdt; Kanika Goel 002; Niels Martin; Pnina Soffer (ACM J. Data Inf. Qual., 2023)

Supporting data-aware processes with MERODE. - Monique Snoeck; Charlotte Verbruggen; Johannes De Smedt; Jochen De Weerdt (Softw. Syst. Model., 2023)

A Novel Contextualization Method for Process Discovery Using Activity Specialization Hierarchies. - Zahra Ahmadi; Jochen De Weerdt; Estefanía Serral Asensio (BPMDS/EMMSAD@CAiSE, 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)

Multivariate Approaches for Process Model Forecasting. - Yongbo Yu; Jari Peeperkorn; Johannes De Smedt; Jochen De Weerdt (ICPM Workshops, 2024)

Efficient Information Extraction in Few-Shot Relation Classification through Contrastive Representation Learning. - Philipp Borchert; Jochen De Weerdt; Marie-Francine Moens (NAACL (Short Papers), 2024)

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

Native Design Bias: Studying the Impact of English Nativeness on Language Model Performance. - Manon Reusens; Philipp Borchert; Jochen De Weerdt; Bart Baesens (CoRR, 2024)

Dynamic and Scalable Data Preparation for Object-Centric Process Mining. - Lien Bosmans; Jari Peeperkorn; Alexandre Goossens; Giovanni Lugaresi; Johannes De Smedt; Jochen De Weerdt (CoRR, 2024)

Generating Realistic Adversarial Examples for Business Processes using Variational Autoencoders. - Alexander Stevens; Jari Peeperkorn; Johannes De Smedt; Jochen De Weerdt (CoRR, 2024)

Predictive process model monitoring using long short-term memory networks. - Johannes De Smedt; Jochen De Weerdt (Eng. Appl. Artif. Intell., 2024)

Industry-sensitive language modeling for business. - Philipp Borchert; Kristof Coussement; Jochen De Weerdt; Arno De Caigny (Eur. J. Oper. Res., 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)

SHINE: A Scalable Heterogeneous Inductive Graph Neural Network for Large Imbalanced Datasets. - Rafaël Van Belle; Jochen De Weerdt (IEEE Trans. Knowl. Data Eng., 2024)

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

An Expert-Validated Bridging Model for IoT Process Mining. - Yannis Bertrand; Jochen De Weerdt; Estefanía Serral (Bus. Inf. Syst. Eng., 2024)

Language Fusion for Parameter-Efficient Cross-lingual Transfer. - Philipp Borchert; Ivan Vulic; Marie-Francine Moens; Jochen De Weerdt (ACL (1), 2025)

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

SimBank: from Simulation to Solution in Prescriptive Process Monitoring. - Jakob De Moor; Hans Weytjens; Johannes De Smedt; Jochen De Weerdt (CoRR, 2025)

Model-driven Stochastic Trace Clustering. - Jari Peeperkorn; Johannes De Smedt; Jochen De Weerdt (CoRR, 2025)

Linking Actor Behavior to Process Performance Over Time. - Aurélie Leribaux; Rafael Oyamada; Johannes De Smedt; Zahra Dasht Bozorgi; Artem Polyvyanyy; Jochen De Weerdt (CoRR, 2025)