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Deep Learning as a Competitive Feature-Free Approach for Automated Algorithm Selection on the Traveling Salesperson Problem., , , , and . PPSN (1), volume 12269 of Lecture Notes in Computer Science, page 48-64. Springer, (2020)A study on the effects of normalized TSP features for automated algorithm selection., , , , , and . Theor. Comput. Sci., 940 (Part): 123-145 (2023)Promises and pitfalls of deep neural networks in neuroimaging-based psychiatric research., , , , and . CoRR, (2023)On the potential of normalized TSP features for automated algorithm selection., , , , , and . FOGA, page 7:1-7:15. ACM, (2021)<tt>RP-Mod</tt>&<tt>RP-Crowd: </tt> Moderator- and Crowd-Annotated German News Comment Datasets., , , , , and . NeurIPS Datasets and Benchmarks, (2021)Enhancing Resilience of Deep Learning Networks By Means of Transferable Adversaries., , and . IJCNN, page 1-8. IEEE, (2020)Deep-ELA: Deep Exploratory Landscape Analysis with Self-Supervised Pretrained Transformers for Single- and Multi-Objective Continuous Optimization Problems., , and . CoRR, (2024)FakeYou! - A Gamified Approach for Building and Evaluating Resilience Against Fake News., , , , , , and . MISDOOM, volume 12259 of Lecture Notes in Computer Science, page 218-232. Springer, (2020)Artificial Social Media Campaign Creation for Benchmarking and Challenging Detection Approaches., , , , and . ICWSM Workshops, (2022)Towards Feature-Free Automated Algorithm Selection for Single-Objective Continuous Black-Box Optimization., , , and . SSCI, page 1-8. IEEE, (2021)