Quantile Encoder: Tackling High Cardinality Categorical Features in Regression Problems. - Carlos Mougan; David Masip; Jordi Nin; Oriol Pujol (MDAI, 2021)

Fairness implications of encoding protected categorical attributes. - Carlos Mougan; José M. Álvarez 002; Gourab K. Patro; Salvatore Ruggieri; Steffen Staab (CoRR, 2022)

Explanation Shift: Detecting distribution shifts on tabular data via the explanation space. - Carlos Mougan; Klaus Broelemann; Gjergji Kasneci; Thanassis Tiropanis; Steffen Staab (CoRR, 2022)

Monitoring Model Deterioration with Explainable Uncertainty Estimation via Non-parametric Bootstrap. - Carlos Mougan; Dan Saattrup Nielsen (AAAI, 2023)

Fairness Implications of Encoding Protected Categorical Attributes. - Carlos Mougan; José M. Álvarez 002; Salvatore Ruggieri; Steffen Staab (AIES, 2023)

How to Data in Datathons. - Carlos Mougan; Richard Plant; Clare Teng; Marya Bazzi; Alvaro Cabrejas Egea; Ryan Sze-Yin Chan; David Salvador Jasin; Martin Stoffel; Kirstie J. Whitaker; Jules Manser (NeurIPS, 2023)

Demographic Parity Inspector: Fairness Audits via the Explanation Space. - Carlos Mougan; Laura State; Antonio Ferrara 003; Salvatore Ruggieri; Steffen Staab (CoRR, 2023)

Explanation Shift: Investigating Interactions between Models and Shifting Data Distributions. - Carlos Mougan; Klaus Broelemann; David Masip; Gjergji Kasneci; Thanassis Tiropanis; Steffen Staab (CoRR, 2023)

The Role of Large Language Models in the Recognition of Territorial Sovereignty: An Analysis of the Construction of Legitimacy. - Francisco Castillo-Eslava; Carlos Mougan; Alejandro Romero-Reche; Steffen Staab (CoRR, 2023)

AI and the EU Digital Markets Act: Addressing the Risks of Bigness in Generative AI. - Ayse Gizem Yasar; Andrew Chong; Evan Dong; Thomas Krendl Gilbert; Sarah Hladikova; Roland Maio; Carlos Mougan; Xudong Shen; Shubham Singh; Ana-Andreea Stoica; Savannah Thais; Miri Zilka (CoRR, 2023)

Kantian Deontology Meets AI Alignment: Towards Morally Robust Fairness Metrics. - Carlos Mougan; Joshua Brand (CoRR, 2023)

Model Agnostic Explainable Selective Regression via Uncertainty Estimation. - Andrea Pugnana; Carlos Mougan; Dan Saattrup Nielsen (CoRR, 2023)

Policy Advice and Best Practices on Bias and Fairness in Artificial Intelligence. - José M. Álvarez 002; Alejandra Bringas Colmenarejo; Alaa Elobaid; Simone Fabbrizzi; Miriam Fahimi; Antonio Ferrara 003; Siamak Ghodsi; Carlos Mougan; Ioanna Papageorgiou; Paula Reyero Lobo; Mayra Russo; Kristen M. Scott; et al. (EWAF, 2024)

Moral Persuasion in Large Language Models: Evaluating Susceptibility and Ethical Alignment. - Allison Huang; Yulu Niki Pi; Carlos Mougan (CoRR, 2024)

Policy advice and best practices on bias and fairness in AI. - José M. Álvarez 002; Alejandra Bringas Colmenarejo; Alaa Elobaid; Simone Fabbrizzi; Miriam Fahimi; Antonio Ferrara 003; Siamak Ghodsi; Carlos Mougan; Ioanna Papageorgiou; Paula Reyero Lobo; Mayra Russo; Kristen M. Scott; et al. (Ethics Inf. Technol., 2024)

Explanation Shift: How Did the Distribution Shift Impact the Model? - Carlos Mougan; Klaus Broelemann; Gjergji Kasneci; Thanassis Tiropanis; Steffen Staab (Trans. Mach. Learn. Res., 2025)

Model Monitoring in the Absence of Labeled Data via Feature Attributions Distributions. - Carlos Mougan (CoRR, 2025)

Measuring Fairness in Financial Transaction Machine Learning Models. - Deniz Sezin Ayvaz; Lorenzo Belenguer; Hankun He; Deborah Dormah Kanubala; Mingxu Li; Soung Low; Carlos Mougan; Faithful Chiagoziem Onwuegbuche; Yulu Pi; Natalia Sikora; Dan Tran; Shresth Verma; et al. (CoRR, 2025)