| 2026 | Random Unicycle Network (RUN!): supercharging harmonic oscillator networks via non-holonomic constraints. | Mariano Ramrez Montero, Andrea Ceni, Andrea Cossu, Davide Bacciu, Claudio Gallicchio, Cosimo Della Santina |
| 2026 | Learning Counterfactual Densities via Marginal Contrastive Discrimination. | Katia Meziani, Aminata Ndiaye, Madalina Olteanu |
| 2026 | Label-Efficient and Adaptable Image Selection for Large-Scale E-Commerce Catalogs. | Maytal Messing, Guy Shani |
| 2026 | Fast denoising of low-count Monte Carlo proton therapy dose distributions with ResUNet. | Pierre Merveille, Ana Maria Barragn-Montero, Kevin Souris, John A. Lee |
| 2026 | Constraint Guided Recurrent Convolutional AutoEncoders for Condition Indicator Estimation. | Maarten Meire, Quinten Van Baelen, Ted Ooijevaar, Peter Karsmakers |
| 2026 | Self-Certified Deep Metric Learning with N-Tuple Losses. | Oritsemisan Meggison, Sijia Zhou, Ata Kabn |
| 2026 | Context-Aware Graph Attention for Unsupervised Telco Anomaly Detection. | Sara Malacarne, Eirik Hoel-Hiseth, David Zsolt Biro, Erlend Aune, Massimiliano Ruocco |
| 2026 | Hierarchical Multi-Scale Deep Neural Network for Schizophrenia Detection in Neuroimaging. | Carlos Dias Maia, Gabriel Barbosa da Fonseca, Luis Enrique Zrate Glvez, Silvio Jamil Ferzoli Guimares |
| 2026 | Boosting the Lottery Ticket Hypothesis with Knowledge Distillation: Finding Sparser Winning Tickets. | Daan Luyckx, Peter Karsmakers |
| 2026 | Interpreting Logical Explanations of Classifying Neural Networks. | Fabrizio Leopardi, Faezeh Labbaf, Toms Kolrik, Michael Wand, Natasha Sharygina |
| 2026 | Multi-Scale Stochastic Neighbor Embedding with Twice Adaptive Bandwidths. | John A. Lee, Pierre Lambert, Edouard Couplet, Pierre Merveille, Dounia Mulders, Cyril de Bodt, Michel Verleysen |
| 2026 | Domination Reliability Analysis Based on Graph Features Using Generalized Matrix LVQ. | Mandy Lange-Geisler, Klaus Dohmen, Thomas Villmann |
| 2026 | Drift-Aware Evaluation of Fair Stream Learning. | Kathrin Lammers, Fabian Hinder, Barbara Hammer, Valerie Vaquet |
| 2026 | RKLU: Redistributive KL Distillation for Efficient Retain-Free Machine Unlearning. | Varun Sampath Kumar, Esmaeil S. Nadimi, Vinay Chakravarthi Gogineni |
| 2026 | Linear Evaluation Complexity of Surrogate-Assisted (1+1)-EA on OneMax. | Oliver Kramer |
| 2026 | LMAP: Local PCA Models with Global MDS Embeddings. | Oliver Kramer |
| 2026 | Techniques for Reliable, Safe and Robust AI Applications. | Caroline Knig, Cecilio Angulo, Pedro Jess Copado, Ganesh Kumar Venayagamoorthy |
| 2026 | A New Positional Encoding Loss for Anomaly Transformer in Time series Anomaly Detection. | Quan Khuu, Huynh Ngu |
| 2026 | DeepFedNAS: Pareto Optimal Supernet Training for Improved and Predictor-Free Federated Neural Architecture Search. | Bostan Khan, Masoud Daneshtalab |
| 2026 | Enforcing Feature Sparseness for Reliable Classification by Prototype-Based Models. | Marika Kaden, Julius Voigt, Sascha Saralajew, Thomas Villmann |
| 2026 | Geometric-analytical Generation of Counterfactuals for Prototype-based Classifiers. | Marika Kaden, Lynn V. Reuss, Thomas Villmann |
| 2026 | Reliable Counterfactuals for Machine Learning Models - Current Aspects and Perspectives. | Marika Kaden, Benjamin Paassen, Barbara Hammer, Ronny Schubert, Thomas Villmann |
| 2026 | Evaluation of Rashomon Sets for the Determination of Stable and Plausible Model Explanations. | Marika Kaden, Mahrokh Karimi, Subhashree Panda, Thomas Pfaff, Thomas Villmann |
| 2026 | Model Sees but Does Not Learn: Eliminating Error Propagation in Reasoning Distillation. | Jaeeun Jang, Hansle Lee, Wonjun Cho, Sangmin Kim |
| 2026 | Graph Representation Learning for Software Architecture Recovery. | Rakhshanda Jabeen, Morgan Ericsson, Jonas Nordqvist, Anna Wingkvist |