161 citations · 199 across the 5 of their papers we have counts for
6 papers
Equivariance by Contrast: Identifiable Equivariant Embeddings from Unlabeled Finite Group Actions
Tobias Schmidt, Steffen Schneider, Matthias Bethge
We propose Equivariance by Contrast (EbC) to learn equivariant embeddings from observation pairs , where is drawn from a finite group acting o…
RDumb: A simple approach that questions our progress in continual test-time adaptation
Ori Press, Steffen Schneider, Matthias Kümmerer +1
Test-Time Adaptation (TTA) allows to update pre-trained models to changing data distributions at deployment time. While early work tested these algorithms for individual fixed dist…
If your data distribution shifts, use self-learning
Evgenia Rusak, Steffen Schneider, George Pachitariu +5
We demonstrate that self-learning techniques like entropy minimization and pseudo-labeling are simple and effective at improving performance of a deployed computer vision model und…
Contrastive Learning Inverts the Data Generating Process
Roland S. Zimmermann, Yash Sharma, Steffen Schneider +2
Contrastive learning has recently seen tremendous success in self-supervised learning. So far, however, it is largely unclear why the learned representations generalize so effectiv…
Improving robustness against common corruptions by covariate shift adaptation
Steffen Schneider, Evgenia Rusak, Luisa Eck +3
Today's state-of-the-art machine vision models are vulnerable to image corruptions like blurring or compression artefacts, limiting their performance in many real-world application…
wav2vec: Unsupervised Pre-training for Speech Recognition
Steffen Schneider, Alexei Baevski, Ronan Collobert +1
We explore unsupervised pre-training for speech recognition by learning representations of raw audio. wav2vec is trained on large amounts of unlabeled audio data and the resulting…