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Interpreting Black-box Machine Learning Models for High Dimensional Datasets2023 IEEE International Conference on Data Science and Advanced Analytics (DSAA) conference-paper Computer Science Explainable Artificial Intelligence (XAI) Open access
Md Shajalal, Alexander Graß, Till Döhmen, Sisay Adugna Chala, Alexander Boden, Christian Beecks, +1 more
19citations -
COOD: Combined out-of-distribution detection using multiple measures for anomaly & novel class detection in large-scale hierarchical classification2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) conference-paper Computer Science Adversarial Robustness in Machine Learning Open access
Laurens Hogeweg, Rajesh Gangireddy, Django Brunink, Vincent J. Kalkman, L. J. Cornelissen, Jacob W. Kamminga
5citations -
COOD: Combined out-of-distribution detection using multiple measures for anomaly & novel class detection in large-scale hierarchical classification2024 arXiv (Cornell University) preprint Computer Science Adversarial Robustness in Machine Learning Open access
Laurens Hogeweg, Rajesh Gangireddy, Django Brunink, Vincent J. Kalkman, L. J. Cornelissen, Jacob W. Kamminga
2citations -
PS-AAS: Portfolio Selection for Automated Algorithm Selection in Black-Box Optimization - Reproducibility Repository2023 Zenodo (CERN European Organization for Nuclear Research) article Computer Science Metaheuristic Optimization Algorithms Research Open access
Ana Kostovska, Gjorgjina Cenikj, Diederick Vermetten, Anja Jankovič, Ana Nikolikj, Urban Škvorc, +3 more
0citations
4 results