Graduate School of Systemic Neurosciences GSN-LMU
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Steffen Schneider

Dr. Steffen Schneider

GSN associate ("außerordentlich") faculty

Responsibilities

Research Group Leader (Tenure Track)

Contact

Helmholtz Center Munich,
Computational Health Center


Website: https://dynamical-inference.ai/

Further Information

Keywords:
dynamical systems, representation learning, neural dynamics, identifiability theory, self-supervised learning, system identification

Brief research description:
We develop machine learning algorithms for representation learning and inference of nonlinear system dynamics, study how large and multi-modal biological datasets can be compressed into foundation models, and study their mechanistic interpretability. An up-to-date description of our research and latest news about publications and preprints is always available on our website: https://dynamical-inference.ai/

Selected publications:

Self-supervised contrastive learning performs non-linear system identification. arXiv, 2024. Rodrigo Gonzalez Laiz*, Tobias Schmidt*, and Steffen Schneider. https://arxiv.org/abs/2410.14673

Neuro-musculoskeletal modeling reveals muscle-level neural dynamics of adaptive learning in sensorimotor cortex. bioRxiv, 2024. Travis DeWolf*, Steffen Schneider*, Paul Soubiran, Adrian Roggenbach, and Mackenzie W Mathis. https://doi.org/10.1101/2024.09.11.612513

Learnable latent embeddings for joint behavioural and neural analysis. Nature, 2023. Steffen Schneider*, Jin Hwa Lee*, and Mackenzie W. Mathis. https://doi.org/10.1038/s41586-023-06031-6

Contrastive Learning Inverts the Data Generating Process. International Conference on Machine Learning (ICML), 2021. Roland Zimmermann*, Yash Sharma*, Steffen Schneider*, Matthias Bethge, and Wieland Brendel. https://doi.org/10.48550/arXiv.2102.08850 wav2vec:

Unsupervised Pre-training for Speech Recognition. Interspeech, 2019. Steffen Schneider, Alexei Baevski, Ronan Collobert, Michael Auli. https://doi.org/10.48550/arXiv.1904.05862