Thomas Robert Altstidl

Machine Learning and Data Analytics Lab

On the Scalability of Certified Adversarial Robustness with Generated Data (2024) Altstidl TR, Dobre D, Kosmala A, Eskofier B, Gidel G, Schwinn L Conference contribution, Original article The Impact of Random Models on Standardized Clustering Similarity (2024) Klede K, Altstidl TR, Zanca D, Eskofier B Journal article, Original article Non-Line-of-Sight Detection for Radio Localization using Deep State Space Models (2024) Brasseler L, Stahlke M, Altstidl TR, Feigl T, Mutschler C Conference contribution, Original article Large-Scale Dataset Pruning in Adversarial Training through Data Importance Extrapolation (2024) Nieth B, Altstidl TR, Schwinn L, Eskofier B Conference contribution, Conference Contribution How Intermodal Interaction Affects the Performance of Deep Multimodal Fusion for Mixed-Type Time Series (2024) Dietz S, Altstidl TR, Zanca D, Eskofier B, Nguyen A Conference contribution, Conference Contribution p-value Adjustment for Monotonous, Unbiased, and Fast Clustering Comparison (2023) Klede K, Altstidl TR, Zanca D, Eskofier B Conference contribution, Original article Just a Matter of Scale? Reevaluating Scale Equivariance in Convolutional Neural Networks (2023) Altstidl TR, Nguyen A, Schwinn L, Köferl F, Mutschler C, Eskofier B, Zanca D Conference contribution, Original article Fetal Re-Identification in Multiple Pregnancy Ultrasound Images Using Deep Learning (2023) Gabler E, Nissen M, Altstidl TR, Titzmann A, Packhäuser K, Maier A, Fasching P, et al. Conference contribution, Conference Contribution In Vivo Skin-Type Classification Using Millimeter-Wave Near-Field Probe Spectroscopy (2022) Hecht D, Pfahler T, Ullmann I, Altstidl TR, Amer N, Jin Y, Eskofier B, Vossiek M Conference contribution Accuracy-Aware Compression of Channel Impulse Responses using Deep Learning (2021) Altstidl TR, Kram S, Herrmann O, Stahlke M, Feigl T, Mutschler C Conference contribution, Conference Contribution