7 citations · 20 across the 8 of their papers we have counts for
3 papers · 1 filter
On convex decision regions in deep network representations
Lenka Tětková, Thea Brüsch, Teresa Karen Scheidt +5
Current work on human-machine alignment aims at understanding machine-learned latent spaces and their correspondence to human representations. G{ä}rdenfors' conceptual spaces is a…
Robustness of Visual Explanations to Common Data Augmentation
Lenka Tětková, Lars Kai Hansen
As the use of deep neural networks continues to grow, understanding their behaviour has become more crucial than ever. Post-hoc explainability methods are a potential solution, but…
On the role of Model Uncertainties in Bayesian Optimization
Jonathan Foldager, Mikkel Jordahn, Lars Kai Hansen +1
Bayesian optimization (BO) is a popular method for black-box optimization, which relies on uncertainty as part of its decision-making process when deciding which experiment to perf…