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  • CEBRA
    CEBRA is a machine-learning method that can be used to compress time series in a way that reveals otherwise hidden structures in the variability of the data It excels on behavioural and neural data recorded simultaneously
  • Learnable latent embeddings for joint behavioural and neural analysis
    A new encoding method, CEBRA, jointly uses behavioural and neural data in a (supervised) hypothesis- or (self-supervised) discovery-driven manner to produce both consistent and high-performance
  • GitHub - AdaptiveMotorControlLab CEBRA: Learnable latent embeddings for . . .
    cebra is a patented self-supervised method for non-linear clustering that allows for label-informed time series analysis It can jointly use behavioral and neural data in a hypothesis- or discovery-driven manner to produce consistent, high-performance latent spaces
  • Cebra - Wikipedia, la enciclopedia libre
    En la actualidad, la cebra con la difusión más amplia es la cebra común Viven desde las zonas de transición entre la sabana y el desierto del sur de Sudán y de Etiopía, pasando por la sabana de África oriental, hasta el sur y el suroeste del continente
  • Cebra - Características, dónde vive, qué come y reproducción
    Descubre las características de la cebra, dónde vive, qué come, cómo se reproduce y a qué amenazas se enfrenta La cebra es un mamífero herbívoro, de color negro con rayas blancas
  • Using CEBRA-Time to Identify Latent Embeddings — OpenScope Databook
    We utilize CEBRA-Time to create a 3D latent embedding space of a mouse’s neural activity while passively viewing visual stimuli This algorithm can help us identify patterns in neural activity and its relationship to the visual stimulus
  • Learnable latent embeddings for joint behavioral and neural analysis
    Here, we fill this gap with a novel method, CEBRA, that jointly uses behavioral and neural data in a hypothesis- or discovery-driven manner to produce consistent, high-performance latent spaces
  • Welcome to CEBRA’s documentation!
    CEBRA is a library for estimating Consistent EmBeddings of high-dimensional Recordings using Auxiliary variables It contains self-supervised learning algorithms implemented in PyTorch, and has support for a variety of different datasets common in biology and neuroscience
  • cebra_time. ipynb - Colab
    We utilize CEBRA-Time to create a 3D latent embedding space of a mouse’s neural activity while passively viewing visual stimuli This algorithm can help us identify patterns in neural activity
  • Brain dynamics uncovered using a machine-learning algorithm
    CEBRA is a machine-learning method that can be used to compress time series in a way that reveals otherwise hidden structures in the variability of the data





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