56 citations · 140 across the 23 of their papers we have counts for
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stat.ML2022★ 3 cited
On the Identifiability and Estimation of Causal Location-Scale Noise Models
Alexander Immer, Christoph Schultheiss, Julia E. Vogt +3
We study the class of location-scale or heteroscedastic noise models (LSNMs), in which the effect can be written as a function of the cause and a noise source independe…
stat.ML2022★ 11 cited
Invariance Learning in Deep Neural Networks with Differentiable Laplace Approximations
Alexander Immer, Tycho F. A. van der Ouderaa, Gunnar Rätsch +2
Data augmentation is commonly applied to improve performance of deep learning by enforcing the knowledge that certain transformations on the input preserve the output. Currently, t…