WaLRUS: Wavelets for Long-range Representation Using SSMs

Neural Information Processing Systems 

State-Space Models (SSMs) have proven to be powerful tools for modeling longrange dependencies in sequential data. While the recent method known as HiPPO has demonstrated strong performance, and formed the basis for machine learning models S4 and Mamba, it remains limited by its reliance on closed-form solutions for a few specific, well-behaved bases.

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