Dynamical Inference
Schneider LabWe build machine learning algorithms for representation learning and inference of nonlinear system dynamics. We apply these algorithms to model complex biological systems in neuroscience, cell biology and other life science applications.
We build machine learning algorithms for representation learning and inference of nonlinear system dynamics. We apply these algorithms to model complex biological systems in neuroscience, cell biology and other life science applications.
Our Researchers
Publications
Steffen Schneider, Jin H Lee, Mackenzie W Mathis. Learnable Latent Embeddings for Joint Behavioral and Neural Analysis. Nature, 2023.
Roland S Zimmermann, Yash Sharma, Steffen Schneider, Matthias Bethge, Wieland Brendel.Contrastive Learning Inverts the Data Generating Process. ICML, 2021.
Steffen Schneider, Evgenia Rusak, Luisa Eck, Oliver Bringmann, Wieland Brendel, Matthias Bethge. Improving Robustness against Common Corruptions by Covariate Shift Adaptation. NeurIPS, 2020.
Steffen Schneider, Alexei Baevski, Ronan Collobert, Michael Auli. wav2vec: Unsupervised Pre-training for Speech Recognition. Interspeech, 2019
