| 2024 | An Interpretable Human-in-the-Loop Process to Improve Medical Image Classification. | Joana Cristo Santos, Miriam Seoane Santos, Pedro Henriques Abreu |
| 2024 | Predicting Performance Drift in AI Models of Healthcare Without Ground Truth Labels. | Ylenia Rotalinti, Puja Myles, Allan Tucker |
| 2024 | Equivariant Parameter Sharing for Porous Crystalline Materials. | Marko Petkovic, Pablo Romero-Marimon, Vlado Menkovski, Sofa Calero |
| 2024 | Predicting the Failure of Component X in the Scania Dataset with Graph Neural Networks. | Maurizio Parton, Andrea Fois, Michelangelo Vegli, Carlo Metta, Marco Gregnanin |
| 2024 | Node Classification in Random Trees. | Wouter W. L. Nuijten, Vlado Menkovski |
| 2024 | Efficient NAS with FaDE on Hierarchical Spaces. | Simon Neumeyer, Julian Stier, Michael Granitzer |
| 2024 | T-DANTE: Detecting Group Behaviour in Spatio-Temporal Trajectories Using Context Information. | Maedeh Nasri, Thomas Maliappis, Carolien Rieffe, Mitra Baratchi |
| 2024 | Super-Resolution Analysis for Landfill Waste Classification. | Matas Molina, Rita P. Ribeiro, Bruno Veloso, Joo Gama |
| 2024 | A Frank System for Co-Evolutionary Hybrid Decision-Making. | Federico Mazzoni, Riccardo Guidotti, Alessio Malizia |
| 2024 | Interpretable Quantile Regression by Optimal Decision Trees. | Valentin Lemaire, Gal Aglin, Siegfried Nijssen |
| 2024 | Unsupervised Representation Learning for Smart Transportation. | Thabang Lebese, Ccile Mattrand, David Clair, Jean-Marc Bourinet, Franois Deheeger |
| 2024 | AHAM: Adapt, Help, Ask, Model Harvesting LLMs for Literature Mining. | Boshko Koloski, Nada Lavrac, Bojan Cestnik, Senja Pollak, Blaz Skrlj, Andrej Kastrin |
| 2024 | Efficient Lookahead Decision Trees. | Harold Silvre Kiossou, Pierre Schaus, Siegfried Nijssen, Gal Aglin |
| 2024 | Subgraph Mining for Graph Neural Networks. | Adem Kikaj, Giuseppe Marra, Luc De Raedt |
| 2024 | Learning Curve Extrapolation Methods Across Extrapolation Settings. | Lionel Kielhfer, Felix Mohr, Jan N. van Rijn |
| 2024 | Beyond Words: A Comparative Analysis of LLM Embeddings for Effective Clustering. | Imed Keraghel, Stanislas Morbieu, Mohamed Nadif |
| 2024 | Mind the Data, Measuring the Performance Gap Between Tree Ensembles and Deep Learning on Tabular Data. | Axel Karlsson, Tianze Wang, Slawomir Nowaczyk, Sepideh Pashami, Sahar Asadi |
| 2024 | A Remark on Concept Drift for Dependent Data. | Fabian Hinder, Valerie Vaquet, Barbara Hammer |
| 2024 | Variational Perspective on Fair Edge Prediction. | Antoine Gourru, Charlotte Laclau, Manvi Choudhary, Christine Largeron |
| 2024 | Hybrid Ensemble-Based Travel Mode Prediction. | Pawel Golik, Maciej Grzenda, Elzbieta Sienkiewicz |
| 2024 | Investigating the Relation Between Problem Hardness and QUBO Properties. | Thore Gerlach, Sascha Mcke |
| 2024 | Tackling the Abstraction and Reasoning Corpus (ARC) with Object-Centric Models and the MDL Principle. | Sbastien Ferr |
| 2024 | FLocalX - Local to Global Fuzzy Explanations for Black Box Classifiers. | Guillermo Fernndez, Riccardo Guidotti, Fosca Giannotti, Mattia Setzu, Juan A. Aledo, Jos A. Gmez, Jos M. Puerta |
| 2024 | A Structural-Clustering Based Active Learning for Graph Neural Networks. | Ricky Maulana Fajri, Yulong Pei, Lu Yin, Mykola Pechenizkiy |
| 2024 | Monitoring Concept Drift in Continuous Federated Learning Platforms. | Christoph Dsing, Philipp Cimiano |