Xenia Heilmann

According to our database, Xenia Heilmann authored at least 10 papers between 2024 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

From If-Statements to ML Pipelines: Revisiting Bias in Code-Generation.

Minh Duc Bui, Xenia Heilmann, Mattia Cerrato, Manuel Mager, Katharina von der Wense

CoRR, April, 2026

FeDa4Fair: Client-Level Federated Datasets for Fairness Evaluation.

Xenia Heilmann, Luca Corbucci, Mattia Cerrato, Anna Monreale

Proceedings of the 2026 ACM Conference on Fairness, Accountability, and Transparency, 2026

Rashomon Sets and Model Multiplicity in Federated Learning.

Xenia Heilmann, Luca Corbucci, Mattia Cerrato

Proceedings of the 2026 ACM Conference on Fairness, Accountability, and Transparency, 2026

2025

N-Parties Private Structure and Parameter Learning for Sum-Product Networks.

Xenia Heilmann, Ernst Althaus, Mattia Cerrato, Nick Johannes Peter Rassau, Mohammad Sadeq Dousti, Stefan Kramer

CoRR, October, 2025

A Neurosymbolic Approach to Counterfactual Fairness.

Xenia Heilmann, Chiara Manganini, Mattia Cerrato, Vaishak Belle

Proceedings of The 19th International Conference on Neurosymbolic Learning and Reasoning (NeSy 2025), 2025

Corrigendum to Studying Privacy Aspects of Learned Knowledge Bases in the Context of Synthetic and Medical Data.

Xenia Heilmann, Valentin Henkys, Daan Apeldoorn, Konstantin Strauch, Bertil Schmidt, Timm Lilienthal, Torsten Panholzer

Proceedings of the German Medical Data Sciences 2025: GMDS Illuminates Health, 2025

Benefits of the Federation? Analyzing the Impact of Fair Federated Learning at the Client Level.

Luca Corbucci, Xenia Heilmann, Mattia Cerrato

Proceedings of the 2025 ACM Conference on Fairness, Accountability, and Transparency, 2025

A Benchmark for Client-level Fairness in Federated Learning.

Xenia Heilmann, Luca Corbucci, Mattia Cerrato

Proceedings of the European Workshop on Algorithmic Fairness, 2025

2024

Differentially Private Sum-Product Networks.

Xenia Heilmann, Mattia Cerrato, Ernst Althaus

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Studying Privacy Aspects of Learned Knowledge Bases in the Context of Synthetic and Medical Data.

Xenia Heilmann, Daan Apeldoorn, Konstantin Strauch, Bertil Schmidt, Timm Lilienthal, Torsten Panholzer

Proceedings of the German Medical Data Sciences 2024 - Health, 2024