CEBRA

CEBRA

Uncover hidden structures in your data with CEBRA

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CEBRA is a self-supervised learning algorithm that provides interpretable embeddings of high-dimensional recordings using auxiliary variables. It excels in compressing time series data to reveal hidden structures, particularly in behavioral and neural data. The algorithm can decode activity from the visual cortex, reconstruct viewed videos, decode trajectories, and determine position during navigation. CEBRA is a valuable tool for joint behavioral and neural analysis, offering consistent and high-performance latent spaces for hypothesis testing and label-free usage across various datasets and species.

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