Research output per year
Research output per year
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Are Inherently Interpretable Models More Robust? A Study In Music Emotion Recognition
Hoedt, K., Flexer, A. & Widmer, G., 2025, Proceedings of the 22nd Sound and Music Computing Conference 2025 (SMC-25). 8 p.Research output: Chapter in Book/Report/Conference proceeding › Conference proceedings › peer-review
Open Access -
Constructing Adversarial Examples to Investigate The Plausibility of Explanations in Deep Audio And Image Classifiers
Hoedt, K., Praher, V., Flexer, A. & Widmer, G., May 2023, In: Neural Computing and Applications. 35, 14, p. 10011-10029 19 p.Research output: Contribution to journal › Article › peer-review
Open Access -
Concept-Based Techniques for Musicologist-Friendly Explanations In Deep Music Classifiers
Foscarin, F., Hoedt, K., Praher, V., Flexer, A. & Widmer, G., Dec 2022, Proceedings of the 23rd InternationalSociety for Music Information Retrieval Conference (ISMIR 2022). 8 p.Research output: Chapter in Book/Report/Conference proceeding › Conference proceedings › peer-review
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Defending a Music Recommender Against Hubness-Based Adversarial Attacks
Hoedt, K., Flexer, A. & Widmer, G., Jun 2022, Proceedings of the Sound and Music Computing Conference (SMC 2022). Michon, R., Pottier, L. & Orlarey, Y. (eds.). p. 389-394 6 p. (Proceedings of the Sound and Music Computing Conferences).Research output: Chapter in Book/Report/Conference proceeding › Conference proceedings › peer-review
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On End-to-End White-Box Adversarial Attacks in Music Information Retrieval
Prinz, K., Flexer, A. & Widmer, G., 2021, In: Transactions of the International Society of Music Information Retrieval. 1, p. 93-104 12 p.Research output: Contribution to journal › Article › peer-review