Accepted Papers

ACCEPTED PAPERS

Here is the list of this year’s accepted papers:

  1. Predicting and Interpolating Spatiotemporal Environmental Data: A Case Study of Groundwater Storage in Bangladesh
    • Anna Pazola (Brunel University of London)*; Mohammad Shamsudduha (UCL); Richard G. Taylor (UCL); Allan Tucker (Brunel University of London)
  2. Combining Dynamic Bayesian Networks with Population Dynamics Modelling to predict breeding success in seabirds
    • Alan Anderson (University of Aberdeen)*
  3. Bridging Forecast Accuracy and Inventory KPIs: A Simulation-Based Evaluation Framework
    • So Fukuhara (Kagawa University)*; Abdallah Alabdallah (Halmstad University); Nuwan Gunasekara (Halmstad University); Slawomir Nowaczyk (Halmstad University)
  4. LeTMEMo: Leveraging Topic Modeling for Enhancing (Closed-Vocabulary) Models
    • Vu Minh Hoang Dang (University of Houston)*; Rakesh Verma (University of Houston)
  5. Adaptive Local Kernel for Efficient Active Pairwise Constraint Clustering
    • Vincent Blase (IRIT)*; Julien Aligon (IRIT); Moncef Garouani (IRIT); Isabelle Ader-perarnau (INSERM); Olivier Teste (IRIT)
  6. Evidential Deep Learning is not Evidential Learning: A Clear Distinction
    • Arthur Hoarau (CentraleSupélec)*
  7. Enabling Context-Aware Data Reduction
    • Vlada Stegarescu (Akkodis)*; Franck Ravat (IRIT); Jiefu Song (IRIT); Leonidas Papastamatis (Akkodis); Benoit Baurens (Akkodis)
  8. T-SE : A method built on Squeeze-and-Excitation mechanisms for Convolutional Neural Networks’ energy efficiency
    • Noémie Draguet (University of Namur)*; Benoît Frénay (University of Namur)
  9. Detecting Propensity Score Shifts Across Groups in Positive–Unlabeled Data
    • Illia Tesliuk (Institute of Computer Science Polish Academy of Sciences)*; Paweł Teisseyre (Institute of Computer Science Polish Academy of Sciences)
  10. On Sample-Wise Strict Monotonicity with a Gradient Update
    • Ozgur Turan (Delft University of Technology)*; Marco Loog (Radboud University); David Tax (Delft University of Technology)
  11. PromptFusionSR: Multimodal Enhancement of Low‑Resolution Images with Automatic Prompt‑Guided Diffusion
    • Chang QU (University of Technology Sydney); Ilhwan Kwon (University of Technology Sydney); Karthick Thiyagarajan (Western Sydney University); Mukesh Prasad (University of Technology Sydney); Ali Braytee (University of Technology Sydney)*
  12. NTS-DAGMA: A Score-Based Causal Discovery for Anomaly Detection
    • Navin Vincent (Traton AB); Abhishek Srinivasan (KTH, Traton AB)*; Anders Holst (KTH, RISE); Sepideh Pashami (Halmstad University, RISE)
  13. Analyzing Shapley additive explanations to understand anomaly detection algorithms behaviors and their complementarity
    • Jordan Levy (IRIT)*; Paul Saves (IRIT); Moncef Garouani (IRIT); Nicolas Verstaevel (IRIT); Benoit Gaudou (IRIT)
  14. Counterfactual Explanations for Conformal Regression Intervals
    • Aicha Maalej (Jönköping University)*; Ulf Johansson (Jönköping University)
  15. Extending Information Bottleneck Attribution to Video Sequences for Deepfake Detection
    • Veronika Solopova (Technische Universität Berlin)*; Lucas Schmidt (TU Berlin); Vera Schmitt ( Technische Universität Berlin); Dorothea Kolossa (Technische Universität Berlin)
  16. Fast Model Selection for Interpretable Gaussian Process Models using Laplace Approximation
    • Andreas Besginow (Technische Hochschule Ostwestfalen-Lippe)*; Thomas Pawellek (Technische Hochschule Ostwestfalen-Lippe); Jan David Hüwel (Fernuniversität Hagen); Christian Beecks (Fernuniversität Hagen); Markus Lange-Hegermann (Technische Hochschule Ostwestfalen-Lippe)
  17. A Generic Complete Anytime Beam Search for Optimal Decision Tree
    • Harold Kiossou (UCLouvain)*; Pierre Schaus (UCLouvain)
  18. Deep Decision Forest
    • Hugo Starck (Halmstad University); Ngoc Anh Kiet David Tran (Halmstad University); Slawomir Nowaczyk (Halmstad University)*
  19. Graph Neural Networks for Graph-Level Regression on Heterogeneous Network Data: Use Case in Early-Stage Optimization of Software Mapping on Multicore Platforms
    • Oscar ROUSSEL (Nantes University); Zainab GHRAYEB (Nantes University); Sébastien LE NOURS (Nantes University / IETR – UMR CNRS 6164); Christine Sinoquet (University of Nantes)*
  20. Guided Feature Distillation for YOLO11: Efficient Detection of Pseudomonas aeruginosa in High-Resolution Microscopy
    • Mouhcine Ouaaziz (ICube Strasbourg)*; Dimitri Klockenbring (ICube Strasbourg); Joseph Lam-Weil (ICube Strasbourg); Cédric Wemmert (ICube Strasbourg); Benoît Naegel (ICube Strasbourg); Sarah Chouchene (ICube Strasbourg); Morgan Madec (ICube Strasbourg); Winfried Römer (Faculty of Biology, University of Freiburg)
  21. Learning Molecular Structures from Infrared Spectra through Latent Evidence Prediction
    • Sergio Josè Peresson (University of Roma Tor Vergata)*; Danilo Croce (University of Roma Tor Vergata); Roberto Basili (University of Roma Tor Vergata)
  22. E-PAGEC: A Differentiable Joint Attributed-Graph Embedding and Clustering Model
    • Imane Akdim (University Mohammed VI Polytechnic)*; Loubna Mekouar (University Mohammed VI Polytechnic); Youssef Iraqi (University Mohammed VI Polytechnic); Mohamed Nadif (Université Paris Cité)
  23. Exploiting Treatment Similarities for Enhanced Multi-Treatment Uplift Prediction
    • Nathan Le Boudec (Orange)*; Nicolas Voisine (Orange); Bruno Cremilleux (Université de Caen Normandie)
  24. Exceptional Model Residual Mining, and Three Richer EMM Description Languages
    • Aniket Mishra (Technische Universiteit Eindhoven); Cristiana Carbunaru (Technische Universiteit Eindhoven); Wouter Duivesteijn (Technische Universiteit Eindhoven)*
  25. Heterogeneous Pattern Sampling according to Frequency
    • Rayane Lachache (University of Caen Normandy)*; Djawad Bekkoucha (University of Paris-Saclay); Abdelkader Ouali (University of Caen Normandy); Bruno Cremilleux (University of Caen Normandy); Thi-Bich-Hanh Dao (University of Orleans); Christel Vrain (University of Orleans)
  26. Drop the mask! GAMM – A Taxonomy for Graph Attributes Missing Mechanisms
    • Richard Serrano (Laboratoire Hubert Curien)*; Baptiste Jeudy ( Laboratoire Hubert Curien); Charlotte Laclau (Telecom Paris); Christine Largeron (Laboratoire Hubert Curien)
  27. CARTGen-IR: Synthetic Tabular Data Generation for Imbalanced Regression
    • António Pinheiro (Universidade do Porto; INESC TEC)*; Rita Ribeiro (Universidade do Porto; INESC TEC)
  28. Conditional Motif-based Graph Convolutional Network for Anomaly Detection in the Waste Management Network
    • Oliveira, Sara* (INESCTEC); Tabassum, Shazia (INESCTEC)); Gama, Joao (INESCTEC); Garcia, Ana (IGAMAOT); Santana, Pedro (IGAMAOT)
  29. Fair multilayer community detection: A research agenda
    • Georgios Panayiotou (Uppsala University)*; Matteo Magnani (Uppsala University)
  30. An End-to-End Framework for Measuring Product Cannibalization using Multivariate Time Series Forecasting
    • Luis Miguel Matos (University of Minho)*; Daniela Martins (University of Minho)
  31. The Window Dilemma: Why Concept Drift Detection is Ill-Posed
    • Brandon Gower-Winter (Utrecht University)*; Misja Groen (Utrecht University); Georg Krempl (Utrecht University)
  32. Toward Improved Time-Series Explanations for Federated Learning in Healthcare
    • Christoph Düsing (CITEC(Cluster of Excellence Cognitive Interaction Technology), University Bielefeld)*; Philipp Cimiano ( CITEC(Cluster of Excellence Cognitive Interaction Technology), University Bielefeld)
  33. Grasynda: Graph-based Synthetic Time Series Generation
    • Luis Amorim (University of Porto)*; Vítor Cerqueira (University of Porto); Carlos Soares (University of Porto); Paulo Azevedo (University of Minho); Moisés Santos (University of Porto)