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Low-Rank Learning by Design: the Role of Network Architecture and Activation Linearity in Gradient Rank Collapse
Our understanding of learning dynamics of deep neural networks (DNNs) remains incomplete.
CommsVAE: Learning the brain's macroscale communication dynamics using coupled sequential VAEs
To analyze communication, the brain is often split up into anatomical regions that each perform certain computations.
Spatio-temporally separable non-linear latent factor learning: an application to somatomotor cortex fMRI data
Our approach is evaluated on data with multiple motor sub-tasks to assess whether the model captures disentangled latent factors that correspond to each sub-task.
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