113 citations
- University College LondonGB11 papers
- Centre National de la Recherche ScientifiqueFR10 papers
- University of PaduaIT10 papers
- University of Rome Tor VergataIT10 papers
- Vrije Universiteit BrusselBE10 papers
- Chinese University of Hong KongHK9 papers
- Gran Sasso Science InstituteIT9 papers
- National Institute for AstrophysicsIT9 papers
- Rutherford Appleton LaboratoryGB9 papers
- The University of TokyoJP9 papers
- Université de RennesFR9 papers
- Université Paris CitéFR9 papers
9 papers · 1 filter
Detection and Evaluation of Clusters within Sequential Data
Alexander Van Werde, Albert Senen-Cerda, Gianluca Kosmella +1
Sequential data is ubiquitous -- it is routinely gathered to gain insights into complex processes such as behavioral, biological, or physical processes. Challengingly, such data no…
Extracting Money Laundering Transactions from Quasi-Temporal Graph Representation
Haseeb Tariq, Marwan Hassani
Money laundering presents a persistent challenge for financial institutions worldwide, while criminal organizations constantly evolve their tactics to bypass detection systems. Tra…
Chameleons do not Forget: Prompt-Based Online Continual Learning for Next Activity Prediction
Marwan Hassani, Tamara Verbeek, Sjoerd van Straten
Predictive process monitoring (PPM) focuses on predicting future process trajectories, including next activity predictions. This is crucial in dynamic environments where processes…
Towards Privacy-Aware Bayesian Networks: A Credal Approach
Niccolò Rocchi, Fabio Stella, Cassio de Campos
Bayesian networks (BN) are probabilistic graphical models that enable efficient knowledge representation and inference. These have proven effective across diverse domains, includin…
Alternating Bi-Objective Optimization for Explainable Neuro-Fuzzy Systems
Qusai Khaled, Uzay Kaymak, Laura Genga
Fuzzy systems show strong potential in explainable AI due to their rule-based architecture and linguistic variables. Existing approaches navigate the accuracy-explainability trade-…
LOREN: Low Rank-Based Code-Rate Adaptation in Neural Receivers
Bram Van Bolderik, Vlado Menkovski, Sonia Heemstra de Groot +1
Neural network based receivers have recently demonstrated superior system-level performance compared to traditional receivers. However, their practicality is limited by high memory…