8 citations · 16 across the 6 of their papers we have counts for
7 papers
The Surprising Effectiveness of Canonical Knowledge Distillation for Semantic Segmentation
Muhammad Ali, Kevin Alexander Laube, Madan Ravi Ganesh +3
Recent knowledge distillation (KD) methods for semantic segmentation introduce increasingly complex hand-crafted objectives, yet are typically evaluated under fixed iteration sched…
Improving Knowledge Distillation Under Unknown Covariate Shift Through Confidence-Guided Data Augmentation
Niclas Popp, Kevin Alexander Laube, Matthias Hein +1
Large foundation models trained on extensive datasets demonstrate strong zero-shot capabilities in various domains. Knowledge distillation has become an established tool for transf…
Label-free Neural Semantic Image Synthesis
Jiayi Wang, Kevin Alexander Laube, Yumeng Li +4
Recent work has shown great progress in integrating spatial conditioning to control large, pre-trained text-to-image diffusion models. Despite these advances, existing methods desc…
The UniNAS framework: combining modules in arbitrarily complex configurations with argument trees
Kevin Alexander Laube
Designing code to be simplistic yet to offer choice is a tightrope walk. Additional modules such as optimizers and data sets make a framework useful to a broader audience, but the…
Conditional super-network weights
Kevin Alexander Laube, Andreas Zell
Modern Neural Architecture Search methods have repeatedly broken state-of-the-art results for several disciplines. The super-network, a central component of many such methods, enab…
Prune and Replace NAS
Kevin Alexander Laube, Andreas Zell
While recent NAS algorithms are thousands of times faster than the pioneering works, it is often overlooked that they use fewer candidate operations, resulting in a significantly s…
ShuffleNASNets: Efficient CNN models through modified Efficient Neural Architecture Search
Kevin Alexander Laube, Andreas Zell
Neural network architectures found by sophistic search algorithms achieve strikingly good test performance, surpassing most human-crafted network models by significant margins. Alt…