Albatross

Last updated on Oct 7, 2024
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Deep Learning Continual Learning
Tobias Christian Nauen
Tobias Christian Nauen
PhD Student

My research interests include efficiency of machine learning models, multimodal learning, and transformer models.

Publications

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