Publications

Akshay Akshay, Masoud Abedi, Navid Shekarchizadeh, Fiona C Burkhard, Mitali Katoch, Alex Bigger-Allen, Rosalyn M Adam, Katia Monastyrskaya, und Ali Hashemi Gheinani. MLcps: machine learning cumulative performance score for classification problems. GigaScience, (12):giad108, Dezember 2023. [PUMA: MLcps cumulative learning machine performance yaff xack] URL

Lucas Lange, Maurice-Maximilian Heykeroth, und Erhard Rahm. Assessing the Impact of Image Dataset Features on Privacy-Preserving Machine Learning. arXiv preprint arXiv:2409.01329, arXiv, September 2024. [PUMA: (cs.CR) (cs.CV) (cs.LG) Computer Cryptography FOS Pattern Recognition Security Vision area_bigdata area_responsibleai ep information learning machine sciences xack yaff]

Suryanarayana Maddu, Bevan L. Cheeseman, Ivo F. Sbalzarini, und Christian L. Müller. Stability selection enables robust learning of partial differential equations from limited noisy data. arXiv, 2019. [PUMA: (cs.LG) (math.NA) (physics.data-an) Analysis Computer FOS Mathematics Numerical Physical Probability Statistics data information learning machine sciences xack] URL

Veronika Scholz, Peter Winkler, Andreas Hornig, Maik Gude, und Angelos Filippatos. Structural damage identification of composite rotors based on fully connected neural networks and convolutional neural networks. Sensors (Basel), (21)6:2005, MDPI AG, März 2021. [PUMA: (SHM) composite composites; connected convolutional dense fully health machine monitoring neural rotors; structural xack learning networks]

Akshay Akshay, Mitali Katoch, Navid Shekarchizadeh, Masoud Abedi, Ankush Sharma, Fiona C Burkhard, Rosalyn M Adam, Katia Monastyrskaya, und Ali Hashemi Gheinani. Machine Learning Made Easy (MLme): a comprehensive toolkit for machine learning-driven data analysis. Gigascience, (13)Januar 2024. [PUMA: AutoML analysis classification data learning machine problems topic_federatedlearn visualization xack yaff]

Akshay Akshay, Masoud Abedi, Navid Shekarchizadeh, Fiona C Burkhard, Mitali Katoch, Alex Bigger-Allen, Rosalyn M Adam, Katia Monastyrskaya, und Ali Hashemi Gheinani. MLcps: machine learning cumulative performance score for classification problems. Gigascience, (12)Dezember 2022. [PUMA: Python classification evaluation learning machine model package problems score topic_federatedlearn unified xack yaff]

Alina Mailach, und Norbert Siegmund. Socio-Technical Anti-Patterns in Building ML-Enabled Software: Insights from Leaders on the Forefront. 2023 IEEE/ACM 45th International Conference on Software Engineering (ICSE), 690--702, IEEE, Mai 2023. [PUMA: Biological Economics Manuals Pipelines Production Software learning modeling system systems topic_software xack yaff machine]