Unpacking [Digital] Imaginaries. Das Imaginäre im Kontext digitaler Medien
A.L. Menne, C. Schulz, eds., Unpacking [Digital] Imaginaries. Das Imaginäre im Kontext digitaler Medien, Transcript, Bielefeld, n.d.

Responsibilities in sXAI
K.J. Rohlfing, S. Alpsancar, C. Schulte, in: Social Explainable AI, Springer Nature Singapore, Singapore, 2026, pp. 157–177.

The Risk of Manipulation and Deception in sXAI
S. Alpsancar, M. Klenk, in: Social Explainable AI, Springer Nature Singapore, Singapore, 2026, pp. 583–616.

Social Explainable AI
K.J. Rohlfing, K. Främling, B. Lim, S. Alpsancar, K. Thommes, eds., Social Explainable AI, Springer Nature Singapore, Singapore, 2026.

Feeds. Ein zentrales Strukturprinzip sozialer Medien
C. Schulz, in: R. Dörre, A. Tuschling (Eds.), Handbuch Social Media: Geschichte – Kultur – Ästhetik, 1st ed., Metzler Verlag, Stuttgart, n.d.

When prediction replaces explanation:  A threat to psychological science 
M. Knauff, M.V. Butz, B. Kaup, W. Kunde, I. Scharlau, Psyarxiv (2026).

AI has never been inherently interpretable: On a paradoxical origin of eXplainable AI (XAI)
F. Beer, C. Schulz, RESET Journal (Recherches Sciences Sociale Sur Internet) Special Issue: Towards New Social and Historical Studies of Artificial Intelligence (n.d.).

Social Context in Human-AI Interaction (HAI): Towards a Theoretical Framework Based on Multi-Perspectival Imaginaries
A.L. Menne, C. Schulz, in: C. Stephanidis, G. Margetis, S. Ntoa, M. Antona, G. Salvendy (Eds.), HCI International 2026 Posters: 28th International Conference on Human-Computer Interaction, HCII 2026, Montreal, QC, Canada, July 26–31, 2026, Proceedings, Part I, Springer International Publishing, 2026, pp. 93–106.

Exact Computation of Any-Order Shapley Interactions for Graph Neural Networks
M. Muschalik, F. Fumagalli, P. Frazzetto, J. Strotherm, L. Hermes, A. Sperduti, E. Hüllermeier, B. Hammer, in: The Thirteenth International Conference on Learning Representations (ICLR), 2025.

Explaining Outliers using Isolation Forest and Shapley Interactions
R. Visser, F. Fumagalli, E. Hüllermeier, B. Hammer, in: Proceedings of the European Symposium on Artificial Neural Networks (ESANN), 2025.

Unifying Feature-Based Explanations with Functional ANOVA and Cooperative Game Theory
F. Fumagalli, M. Muschalik, E. Hüllermeier, B. Hammer, J. Herbinger, in: Proceedings of The 28th International Conference on Artificial Intelligence and Statistics (AISTATS), PMLR, 2025, pp. 5140–5148.

On "Super Likes" and Algorithmic (In)Visibilities: Frictions Between Social and Economic Logics in the Context of Social Media Platforms
C. Schulz, Digital Culture &; Society  2/2023 (2025) 45–68.

Vernakulärer Code oder die Geister, die der Algorithmus rief - digitale Schriftlichkeit im Kontext von sozialen Medienplattformen
C. Schulz, in: M. Bartelmus, A. Nebrig (Eds.), Digitale Schriftlichkeit – Progammieren, Prozessieren und Codieren von Schrift, 1st ed., transcript , Bielefeld, 2024.

Vom foto-sozialen Graph zum Story-Format: Über die Institutionalisierung sozialmedialer Infrastruktur aus dem Geiste der Fotografie
C. Schulz, in: A. Schürmann, K. Yacavone (Eds.), Die Fotografie und ihre Institutionen. Von der Lehrsammlung zum Bundesinstitut , 1st ed., Reimer Verlag, Berlin , 2024.

No learning rates needed: Introducing SALSA - Stable Armijo Line Search Adaptation
P. Kenneweg, T. Kenneweg, F. Fumagalli, B. Hammer, in: 2024 International Joint Conference on Neural Networks (IJCNN), 2024, pp. 1–8.

Beyond TreeSHAP: Efficient Computation of Any-Order Shapley Interactions for Tree Ensembles
M. Muschalik, F. Fumagalli, B. Hammer, E. Huellermeier, in: Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), 2024, pp. 14388–14396.

SVARM-IQ: Efficient Approximation of Any-order Shapley Interactions through Stratification
P. Kolpaczki, M. Muschalik, F. Fumagalli, B. Hammer, E. Huellermeier, in: Proceedings of The 27th International Conference on Artificial Intelligence and Statistics (AISTATS), PMLR, 2024, pp. 3520–3528.

KernelSHAP-IQ: Weighted Least Square Optimization for Shapley Interactions
F. Fumagalli, M. Muschalik, P. Kolpaczki, E. Hüllermeier, B. Hammer, in: Proceedings of the 41st International Conference on Machine Learning (ICML), PMLR, 2024, pp. 14308–14342.

shapiq: Shapley interactions for machine learning
M. Muschalik, H. Baniecki, F. Fumagalli, P. Kolpaczki, B. Hammer, E. Huellermeier, in: Advances in Neural Information Processing Systems (NeurIPS), 2024, pp. 130324–130357.

Approximating the shapley value without marginal contributions
P. Kolpaczki, V. Bengs, M. Muschalik, E. Hüllermeier, in: Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), 2024, pp. 13246–13255.