Which Transformer to Favor: A Comparative Analysis of Efficiency in Vision Transformers. - Tobias Christian Nauen; Sebastian Palacio; Andreas Dengel 001 (CoRR, 2023)

TaylorShift: Shifting the Complexity of Self-attention from Squared to Linear (and Back) Using Taylor-Softmax. - Tobias Christian Nauen; Sebastian Palacio; Andreas Dengel 001 (ICPR (6), 2024)

A Low-Resolution Image is Worth 1x1 Words: Enabling Fine Image Super-Resolution with Transformers and TaylorShift. - Sanath Budakegowdanadoddi Nagaraju; Brian B. Moser; Tobias Christian Nauen; Stanislav Frolov; Federico Raue; Andreas Dengel 001 (CoRR, 2024)

Zoomed In, Diffused Out: Towards Local Degradation-Aware Multi-Diffusion for Extreme Image Super-Resolution. - Brian B. Moser; Stanislav Frolov; Tobias Christian Nauen; Federico Raue; Andreas Dengel 001 (CoRR, 2024)

Just Leaf It: Accelerating Diffusion Classifiers with Hierarchical Class Pruning. - Arundhati S. Shanbhag; Brian B. Moser; Tobias Christian Nauen; Stanislav Frolov; Federico Raue; Andreas Dengel 001 (CoRR, 2024)

Distill the Best, Ignore the Rest: Improving Dataset Distillation with Loss-Value-Based Pruning. - Brian B. Moser; Federico Raue; Tobias Christian Nauen; Stanislav Frolov; Andreas Dengel 001 (CoRR, 2024)

Which Transformer to Favor: A Comparative Analysis of Efficiency in Vision Transformers. - Tobias Christian Nauen; Sebastian Palacio; Federico Raue; Andreas Dengel 001 (WACV, 2025)

A Study in Dataset Distillation for Image Super-Resolution. - Tobias Dietz; Brian B. Moser; Tobias Christian Nauen; Federico Raue; Stanislav Frolov; Andreas Dengel 001 (CoRR, 2025)

ForAug: Recombining Foregrounds and Backgrounds to Improve Vision Transformer Training with Bias Mitigation. - Tobias Christian Nauen; Brian B. Moser; Federico Raue; Stanislav Frolov; Andreas Dengel 001 (CoRR, 2025)