Taxonomic and Whole Object Constraints: A Deep Architecture. - Mattia Cerrato; Edoardo Arnaudo; Valentina Gliozzi; Roberto Esposito (CogSci, 2019)

Fair pairwise learning to rank. - Mattia Cerrato; Marius Köppel; Alexander Segner; Roberto Esposito; Stefan Kramer 001 (DSAA, 2020)

Constraining deep representations with a noise module for fair classification. - Mattia Cerrato; Roberto Esposito; Laura Li Puma (SAC, 2020)

Ranking Algorithms for Word Ordering in Surface Realization. - Alessandro Mazzei; Mattia Cerrato; Roberto Esposito; Valerio Basile (Inf., 2021)

Fair Group-Shared Representations with Normalizing Flows. - Mattia Cerrato; Marius Köppel; Alexander Segner; Stefan Kramer 001 (CoRR, 2022)

Fair Interpretable Learning via Correction Vectors. - Mattia Cerrato; Marius Köppel; Alexander Segner; Stefan Kramer 001 (CoRR, 2022)

Fair Interpretable Representation Learning with Correction Vectors. - Mattia Cerrato; Alesia Vallenas Coronel; Marius Köppel; Alexander Segner; Roberto Esposito; Stefan Kramer 001 (CoRR, 2022)

Invariant Representations with Stochastically Quantized Neural Networks. - Mattia Cerrato; Marius Köppel; Roberto Esposito; Stefan Kramer 001 (AAAI, 2023)

Privacy-Preserving Learning of Random Forests Without Revealing the Trees. - Lukas-Malte Bammert; Stefan Kramer 001; Mattia Cerrato; Ernst Althaus (DS, 2023)

Hierarchical priors for Hyperspherical Prototypical Networks. - Samuele Fonio; Lorenzo Paletto; Mattia Cerrato; Dino Ienco; Roberto Esposito (ESANN, 2023)

The Case for Correctability in Fair Machine Learning. - Mattia Cerrato; Alesia Vallenas Coronel; Marius Köppel (EWAF, 2023)

Fair Semi-supervised Representation Learning for Tabular Data Classification. - Shuyi Yang; Mattia Cerrato; Dino Ienco; Ruggero G. Pensa; Roberto Esposito (SEBD, 2023)

Automated Scientific Discovery: From Equation Discovery to Autonomous Discovery Systems. - Stefan Kramer 001; Mattia Cerrato; Saso Dzeroski; Ross D. King (CoRR, 2023)

FairSwiRL: fair semi-supervised classification with representation learning. - Shuyi Yang; Mattia Cerrato; Dino Ienco; Ruggero G. Pensa; Roberto Esposito (Mach. Learn., 2023)

Peer Learning: Learning Complex Policies in Groups from Scratch via Action Recommendations. - Cedric Derstroff; Mattia Cerrato; Jannis Brugger; Jan Peters 001; Stefan Kramer 001 (AAAI, 2024)

Science-Gym: A Simple Testbed for AI-Driven Scientific Discovery. - Mattia Cerrato; Nicholas Schmitt; Lennart Baur; Edward Finkelstein; Selina Jukic; Lars Münzel; Felix Peter Paul; Pascal Pfannes; Benedikt Rohr; Julius Schellenberg; Philipp Wolf; Stefan Kramer 001 (DS (1), 2024)

Trust in Fair Algorithms: Pilot Experiment. - Mattia Cerrato; Marius Köppel; Kiara Stempel; Alesia Vallenas Coronel; Niklas Witzig (EWAF, 2024)

Differentially Private Sum-Product Networks. - Xenia Heilmann; Mattia Cerrato; Ernst Althaus (ICML, 2024)

10 Years of Fair Representations: Challenges and Opportunities. - Mattia Cerrato; Marius Köppel; Philipp Wolf; Stefan Kramer 001 (CoRR, 2024)

Predicting NOx emissions in Biochar Production Plants using Machine Learning. - Marius Köppel; Niklas Witzig; Tim Klausmann; Mattia Cerrato; Tobias Schweitzer; Jochen Weber 004; Erdem Yilmaz; Juan Chimbo; Bernardo del Campo; Lissete Davila; David Barreno (CoRR, 2024)

Partitioned least squares. - Roberto Esposito; Mattia Cerrato; Marco Locatelli 001 (Mach. Learn., 2024)

Stochastic Fairness Interventions Are Arbitrary. - Mattia Cerrato; Marius Köppel; Kiara Stempel; Philipp Wolf; Stefan Kramer 001 (EWAF, 2025)

A Benchmark for Client-level Fairness in Federated Learning. - Xenia Heilmann; Luca Corbucci; Mattia Cerrato (EWAF, 2025)

Benefits of the Federation? Analyzing the Impact of Fair Federated Learning at the Client Level. - Luca Corbucci; Xenia Heilmann; Mattia Cerrato (FAccT, 2025)

Neural-Guided Equation Discovery. - Jannis Brugger; Mattia Cerrato; David Richter 001; Cedric Derstroff; Daniel Maninger; Mira Mezini; Stefan Kramer 001 (CoRR, 2025)

FeDa4Fair: Client-Level Federated Datasets for Fairness Evaluation. - Xenia Heilmann; Luca Corbucci; Mattia Cerrato; Anna Monreale (CoRR, 2025)