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Found 3 papers, 3 papers with code
Effectively Modeling Time Series with Simple Discrete State Spaces
For expressivity, we propose a new SSM parameterization based on the companion matrix -- a canonical representation for discrete-time processes -- which enables SpaceTime's SSM layers to learn desirable autoregressive processes.
Hungry Hungry Hippos: Towards Language Modeling with State Space Models
First, we use synthetic language modeling tasks to understand the gap between SSMs and attention.
Ranked #1 on
Language Modelling
on WikiText-103
(using extra training data)
Spatiotemporal Modeling of Multivariate Signals With Graph Neural Networks and Structured State Space Models
Multivariate signals are prevalent in various domains, such as healthcare, transportation systems, and space sciences.
