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Distill the Best, Ignore the Rest: Improving Dataset Distillation with Loss-Value-Based Pruning

We improve dataset distillation by distilling only a representative coreset.

Brian Bernhard Moser, Federico Raue, Tobias Christian Nauen, Stanislav Frolov, Andreas Dengel

Distill the Best, Ignore the Rest: Improving Dataset Distillation with Loss-Value-Based Pruning

Just Leaf It: Accelerating Diffusion Classifiers with Hierarchical Class Pruning

We speed up diffusion classifiers by utilizing a label hierarchy and pruning unrelated paths.

Arundhati S Shanbhag, Brian Bernhard Moser, Tobias Christian Nauen, Stanislav Frolov, Federico Raue, Andreas Dengel

Just Leaf It: Accelerating Diffusion Classifiers with Hierarchical Class Pruning

Zoomed In, Diffused Out: Towards Local Degradation-Aware Multi-Diffusion for Extreme Image Super-Resolution

We extend pretrained super-resolution models to larger images by using local-aware prompts.

Brian B. Moser, Stanislav Frolov, Tobias Christian Nauen, Federico Raue, Andreas Dengel

Zoomed In, Diffused Out: Towards Local Degradation-Aware Multi-Diffusion for Extreme Image Super-Resolution

A Low-Resolution Image is Worth 1x1 Words: Enabling Fine Image Super-Resolution with Transformers and TaylorShift

We utilize the TaylorShift attention mechanism for global pixel-wise-attention in image super-resolution.

Sanath Budakegowdanadoddi Nagaraju, Brian Bernhard Moser, Tobias Christian Nauen, Stanislav Frolov, Federico Raue, Andreas Dengel

Stochastic Control with Signatures

This paper proposes a new method to parameterize open loop controls in stochastic optimal control problems using path signatures. We show that these controls are dense in the space of all admissible controls and establish conditions for stability of the controlled dynamics and target functional.

Peter Bank, Christian Bayer, Paul Peter Hager, Sebastian Riedel, Tobias Christian Nauen