Team JKU-AIWarriors in the ACM Recommender Systems Challenge 2021: Lightweight XGBoost Recommendation Approach Leveraging User Features. - Alexander Krauck; David Penz; Markus Schedl (RecSys Challenge, 2021)

LFM-2b: A Dataset of Enriched Music Listening Events for Recommender Systems Research and Fairness Analysis. - Markus Schedl; Stefan Brandl; Oleg Lesota; Emilia Parada-Cabaleiro; David Penz; Navid Rekabsaz (CHIIR, 2022)

EmoMTB: Emotion-aware Music Tower Blocks. - Alessandro B. Melchiorre; David Penz; Christian Ganhör; Oleg Lesota; Vasco Fragoso; Florian Friztl; Emilia Parada-Cabaleiro; Franz Schubert; Markus Schedl (ICMR, 2022)

Unlearning Protected User Attributes in Recommendations with Adversarial Training. - Christian Ganhör; David Penz; Navid Rekabsaz; Oleg Lesota; Markus Schedl (SIGIR, 2022)

Emotion-aware music tower blocks (EmoMTB ): an intelligent audiovisual interface for music discovery and recommendation. - Alessandro B. Melchiorre; David Penz; Christian Ganhör; Oleg Lesota; Vasco Fragoso; Florian Fritzl; Emilia Parada-Cabaleiro; Franz Schubert; Markus Schedl (Int. J. Multim. Inf. Retr., 2023)

Maximally Expressive GNNs for Outerplanar Graphs. - Franka Bause; Fabian Jogl; Patrick Indri; Tamara Drucks; David Penz; Nils Morten Kriege; Thomas Gärtner 001; Pascal Welke; Maximilian Thiessen (Trans. Mach. Learn. Res., 2025)

Making LLMs Reason? The Intermediate Language Problem in Neurosymbolic Approaches. - Alexander Beiser; David Penz (CoRR, 2025)