New geometric framework simplifies Structured State Space Models

Researchers have introduced a novel geometric framework for constructing discrete-time Structured State Space Models (SSMs), which are foundational to architectures like Mamba. This new approach utilizes a lag operator to derive the discrete-time recurrence directly, offering a more intuitive and modular design. The framework allows for the creation of new SSMs by combining different basis functions and time-warping schemes, with a specific instance shown to precisely replicate the HiPPO model's recurrence. AI

IMPACT Provides new theoretical tools for designing more flexible and robust sequence models, potentially influencing future architectures.

RANK_REASON The cluster contains an academic paper detailing a new theoretical framework for sequence modeling. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.LG →

• Lag Operator SSMs
• Mamba
• Structured State Space Models
• Sutashu Tomonaga

• paper
• model release

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