Accuracy-Aware Compression of Channel Impulse Responses using Deep Learning. - Thomas Altstidl; Sebastian Kram; Oskar Herrmann; Maximilian Stahlke; Tobias Feigl; Christopher Mutschler (IPIN, 2021)

Scaled and Translated Image Recognition (STIR). - Thomas Altstidl; An Nguyen; Leo Schwinn; Franz Köferl; Christopher Mutschler; Björn M. Eskofier; Dario Zanca (Zenodo, 2022)

Scaled and Translated Image Recognition (STIR) Source Data. - Thomas Altstidl; An Nguyen; Leo Schwinn; Franz Köferl; Christopher Mutschler; Björn M. Eskofier; Dario Zanca (Zenodo, 2022)

Fetal Re-Identification in Multiple Pregnancy Ultrasound Images Using Deep Learning. - Elisabeth Gabler; Michael Nissen; Thomas R. Altstidl; Adriana Titzmann; Kai Packhäuser; Andreas K. Maier; Peter A. Fasching; Bjoern M. Eskofier; Heike Leutheuser (EMBC, 2023)

Just a Matter of Scale? Reevaluating Scale Equivariance in Convolutional Neural Networks. - Thomas Altstidl; An Nguyen; Leo Schwinn; Franz Köferl; Christopher Mutschler; Björn M. Eskofier; Dario Zanca (IJCNN, 2023)

p-value Adjustment for Monotonous, Unbiased, and Fast Clustering Comparison. - Kai Klede; Thomas Altstidl; Dario Zanca; Bjoern M. Eskofier (NeurIPS, 2023)

Raising the Bar for Certified Adversarial Robustness with Diffusion Models. - Thomas Altstidl; David Dobre; Björn M. Eskofier; Gauthier Gidel; Leo Schwinn (CoRR, 2023)

Contrastive Language-Image Pretrained Models are Zero-Shot Human Scanpath Predictors. - Dario Zanca; Andrea Zugarini; Simon Dietz; Thomas R. Altstidl; Mark A. Turban Ndjeuha; Leo Schwinn; Bjoern M. Eskofier (CoRR, 2023)

How Intermodal Interaction Affects the Performance of Deep Multimodal Fusion for Mixed-Type Time Series. - Simon Dietz; Thomas Altstidl; Dario Zanca; Björn M. Eskofier; An Nguyen (IJCNN, 2024)

Non-Line-of-Sight Detection for Radio Localization using Deep State Space Models. - Leon Brasseler; Maximilian Stahlke; Thomas Altstidl; Tobias Feigl; Christopher Mutschler (IPIN, 2024)

On the Scalability of Certified Adversarial Robustness with Generated Data. - Thomas Altstidl; David Dobre; Arthur Kosmala; Bjoern M. Eskofier; Gauthier Gidel; Leo Schwinn (NeurIPS, 2024)

The Impact of Random Models on Standardized Clustering Similarity. - Kai Klede; Thomas R. Altstidl; Dario Zanca; Björn M. Eskofier (IEEE Access, 2024)

Large-Scale Dataset Pruning in Adversarial Training through Data Importance Extrapolation. - Björn Nieth; Thomas Altstidl; Leo Schwinn; Björn M. Eskofier (CoRR, 2024)

Caption-Driven Explorations: Aligning Image and Text Embeddings through Human-Inspired Foveated Vision. - Dario Zanca; Andrea Zugarini; Simon Dietz; Thomas R. Altstidl; Mark A. Turban Ndjeuha; Leo Schwinn; Björn M. Eskofier (CoRR, 2024)

ExSMART-PreRA: Explainable Survival and Risk Assessment Using Machine Learning for Time Estimation in Preclinical Rheumatoid Arthritis. - Fatemeh Salehi; Sara Bayat; Georg Schett; Arnd Kleyer; Thomas Altstidl; Bjoern M. Eskofier (IEEE J. Biomed. Health Informatics, 2025)