Context-Based Normalization of Histological Stains Using Deep Convolutional Features. - Daniel Bug; Steffen Schneider 001; Anne Grote; Eva Oswald; Friedrich Feuerhake; Julia Schüler; Dorit Merhof (DLMIA/ML-CDS@MICCAI, 2017)

wav2vec: Unsupervised Pre-Training for Speech Recognition. - Steffen Schneider 001; Alexei Baevski; Ronan Collobert; Michael Auli (INTERSPEECH, 2019)

vq-wav2vec: Self-Supervised Learning of Discrete Speech Representations. - Alexei Baevski; Steffen Schneider 001; Michael Auli (ICLR, 2020)

Improving robustness against common corruptions by covariate shift adaptation. - Steffen Schneider 001; Evgenia Rusak; Luisa Eck; Oliver Bringmann 001; Wieland Brendel; Matthias Bethge (NeurIPS, 2020)

A Primer on Motion Capture with Deep Learning: Principles, Pitfalls and Perspectives. - Alexander Mathis; Steffen Schneider 001; Jessy Lauer; Mackenzie W. Mathis (CoRR, 2020)

Contrastive Learning Inverts the Data Generating Process. - Roland S. Zimmermann; Yash Sharma 001; Steffen Schneider 001; Matthias Bethge; Wieland Brendel (ICML, 2021)

Pretraining boosts out-of-domain robustness for pose estimation. - Alexander Mathis; Thomas Biasi; Steffen Schneider 001; Mert Yüksekgönül; Byron Rogers; Matthias Bethge; Mackenzie W. Mathis (WACV, 2021)

Adapting ImageNet-scale models to complex distribution shifts with self-learning. - Evgenia Rusak; Steffen Schneider 001; Peter V. Gehler; Oliver Bringmann 001; Wieland Brendel; Matthias Bethge (CoRR, 2021)

Learnable latent embeddings for joint behavioral and neural analysis. - Steffen Schneider 001; Jin Hwa Lee; Mackenzie Weygandt Mathis (CoRR, 2022)

If your data distribution shifts, use self-learning. - Evgenia Rusak; Steffen Schneider 001; George Pachitariu; Luisa Eck; Peter Vincent Gehler; Oliver Bringmann 001; Wieland Brendel; Matthias Bethge (Trans. Mach. Learn. Res., 2022)

Unsupervised Object Learning via Common Fate. - Matthias Tangemann; Steffen Schneider 001; Julius von Kügelgen; Francesco Locatello; Peter Vincent Gehler; Thomas Brox; Matthias Kümmerer; Matthias Bethge; Bernhard Schölkopf (CLeaR, 2023)

RDumb: A simple approach that questions our progress in continual test-time adaptation. - Ori Press; Steffen Schneider 001; Matthias Kümmerer; Matthias Bethge (NeurIPS, 2023)

Bildung mit und uber KI in der Schule: Umsetzung einer partizipativen Unterrichtsplattform. - Sarah Schönbrodt; Hanna Dohmen; Paul Pommer; Steffen Schneider 001; Nicolas Berberich; KI macht Schule Team (DELFI Workshops, 2024)

Time-series attribution maps with regularized contrastive learning. - Steffen Schneider 001; Rodrigo González Laiz; Anastasiia Filippova; Markus Frey; Mackenzie W. Mathis (AISTATS, 2025)

Self-supervised contrastive learning performs non-linear system identification. - Rodrigo González Laiz; Tobias Schmidt; Steffen Schneider 001 (ICLR, 2025)