13 citations · 13 across the 3 of their papers we have counts for
3 papers
Birdie: Advancing State Space Models with Reward-Driven Objectives and Curricula
Sam Blouir, Jimmy T. H. Smith, Antonios Anastasopoulos +1
Efficient state space models (SSMs), such as linear recurrent neural networks and linear attention variants, offer computational advantages over Transformers but struggle with task…
Towards a theory of learning dynamics in deep state space models
Jakub Smékal, Jimmy T. H. Smith, Michael Kleinman +2
State space models (SSMs) have shown remarkable empirical performance on many long sequence modeling tasks, but a theoretical understanding of these models is still lacking. In thi…
Convolutional State Space Models for Long-Range Spatiotemporal Modeling
Jimmy T. H. Smith, Shalini De Mello, Jan Kautz +2
Effectively modeling long spatiotemporal sequences is challenging due to the need to model complex spatial correlations and long-range temporal dependencies simultaneously. ConvLST…