Unifying Representations in Neural Models

Unifying Representations in Neural Models

We’re excited to announce that we’re organizing the 4th edition of UniReps as a satellite event in Paris and would love your help in choosing the best date for the community. Your feedback will ensure...

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Biological and neuromorphic recurrent neural networks (RNNs) are subject to spatial and temporal locality constraints on the information that can plausibly be used during learning. A common strategy t...

Recurrent neural networks (RNNs) are powerful models used widely in both machine learning and neuroscience to learn tasks with temporal dependencies and to model neural dynamics. However, despite...