On the optimization of material usage in power transformer manufacturing. - Georgios C. Chasparis; Werner Zellinger; Verena Haunschmid; Markus Riedenbauer; Reinhard Stumptner (IEEE Conf. on Intelligent Systems, 2016)

An Evolutionary Stochastic-Local-Search Framework for One-Dimensional Cutting-Stock Problems. - Georgios C. Chasparis; Michael Rossbory; Verena Haunschmid (CoRR, 2017)

A DaQL to Monitor Data Quality in Machine Learning Applications. - Lisa Ehrlinger; Verena Haunschmid; Davide Palazzini; Christian Lettner (DEXA (1), 2019)

Towards Explainable Music Emotion Recognition: The Route via Mid-level Features. - Shreyan Chowdhury; Andreu Vall; Verena Haunschmid; Gerhard Widmer (ISMIR, 2019)

Emotion and Theme Recognition in Music with Frequency-Aware RF-Regularized CNNs. - Khaled Koutini; Shreyan Chowdhury; Verena Haunschmid; Hamid Eghbal-Zadeh; Gerhard Widmer (MediaEval, 2019)

Two-level Explanations in Music Emotion Recognition. - Verena Haunschmid; Shreyan Chowdhury; Gerhard Widmer (CoRR, 2019)

Anomalous Sound Detection as a Simple Binary Classification Problem with Careful Selection of Proxy Outlier Examples. - Paul Primus; Verena Haunschmid; Patrick Praher; Gerhard Widmer (DCASE, 2020)

On Data Augmentation and Adversarial Risk: An Empirical Analysis. - Hamid Eghbal-zadeh; Khaled Koutini; Paul Primus; Verena Haunschmid; Michal Lewandowski; Werner Zellinger; Bernhard Alois Moser; Gerhard Widmer (CoRR, 2020)

Receptive-Field Regularized CNNs for Music Classification and Tagging. - Khaled Koutini; Hamid Eghbal-Zadeh; Verena Haunschmid; Paul Primus; Shreyan Chowdhury; Gerhard Widmer (CoRR, 2020)

audioLIME: Listenable Explanations Using Source Separation. - Verena Haunschmid; Ethan Manilow; Gerhard Widmer (CoRR, 2020)

Towards Musically Meaningful Explanations Using Source Separation. - Verena Haunschmid; Ethan Manilow; Gerhard Widmer (CoRR, 2020)

LEMONS: Listenable Explanations for Music recOmmeNder Systems. - Alessandro B. Melchiorre; Verena Haunschmid; Markus Schedl; Gerhard Widmer (ECIR (2), 2021)