Language Models for Next-Track Music Recommendation. - Maximilian Mayerl; Michael Vötter; Eva Zangerle; Günther Specht (Grundlagen von Datenbanken, 2019)

Autoencoders for Next-Track-Recommendation. - Michael Vötter; Eva Zangerle; Maximilian Mayerl; Günther Specht (Grundlagen von Datenbanken, 2019)

Hit Song Prediction: Leveraging Low- and High-Level Audio Features. - Eva Zangerle; Michael Vötter; Ramona Huber; Yi-Hsuan Yang (ISMIR, 2019)

MediaEval 2019 Emotion and Theme Recognition task: A VQ-VAE Based Approach. - Hsiao-Tzu Hung; Yu-Hua Chen; Maximilian Mayerl; Michael Vötter; Eva Zangerle; Yi-Hsuan Yang (MediaEval, 2019)

Recognizing Song Mood and Theme Using Convolutional Recurrent Neural Networks. - Maximilian Mayerl; Michael Vötter; Hsiao-Tzu Hung; Bo-Yu Chen; Yi-Hsuan Yang; Eva Zangerle (MediaEval, 2019)

Recognizing Song Mood and Theme: Leveraging Ensembles of Tag Groups. - Michael Vötter; Maximilian Mayerl; Günther Specht; Eva Zangerle (MediaEval, 2020)

Novel Datasets for Evaluating Song Popularity Prediction Tasks. - Michael Vötter; Maximilian Mayerl; Günther Specht; Eva Zangerle (ISM, 2021)

Recognizing Song Mood and Theme: Clustering-based Ensembles. - Maximilian Mayerl; Michael Vötter; Andreas Peintner; Günther Specht; Eva Zangerle (MediaEval, 2021)

HSP Datasets: Insights on Song Popularity Prediction. - Michael Vötter; Maximilian Mayerl; Günther Specht; Eva Zangerle (Int. J. Semantic Comput., 2022)

Pairwise Learning to Rank for Hit Song Prediction. - Maximilian Mayerl; Michael Vötter; Günther Specht; Eva Zangerle (BTW, 2023)