Theoretical Foundations of Deep Selective State-Space Models

Theoretical Foundations of Deep Selective State-Space Models

29 February 2024

Nicola Muca Cirone

Antonio Orvieto

Benjamin Walker

Papers citing "Theoretical Foundations of Deep Selective State-Space Models"

7 / 7 papers shown

Title
From S4 to Mamba: A Comprehensive Survey on Structured State Space Models Shriyank Somvanshi Md Monzurul Islam Mahmuda Sultana Mimi Sazzad Bin Bashar Polock Gaurab Chhetri Subasish Das Mamba AI4TS 37 0 0 22 Mar 2025
From Markov to Laplace: How Mamba In-Context Learns Markov Chains Marco Bondaschi Nived Rajaraman Xiuying Wei Kannan Ramchandran Razvan Pascanu Çağlar Gülçehre Michael C. Gastpar Ashok Vardhan Makkuva 58 0 0 17 Feb 2025
Unlocking State-Tracking in Linear RNNs Through Negative Eigenvalues Riccardo Grazzi Julien N. Siems Jörg K.H. Franke Arber Zela Frank Hutter Massimiliano Pontil 84 10 0 19 Nov 2024
Understanding the differences in Foundation Models: Attention, State Space Models, and Recurrent Neural Networks Jerome Sieber Carmen Amo Alonso A. Didier M. Zeilinger Antonio Orvieto AAML 34 7 0 24 May 2024
Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models Soham De Samuel L. Smith Anushan Fernando Aleksandar Botev George-Christian Muraru ... David Budden Yee Whye Teh Razvan Pascanu Nando de Freitas Çağlar Gülçehre Mamba 51 116 0 29 Feb 2024
Resurrecting Recurrent Neural Networks for Long Sequences Antonio Orvieto Samuel L. Smith Albert Gu Anushan Fernando Çağlar Gülçehre Razvan Pascanu Soham De 83 258 0 11 Mar 2023
Structured State Space Models for In-Context Reinforcement Learning Chris Xiaoxuan Lu Yannick Schroecker Albert Gu Emilio Parisotto Jakob N. Foerster Satinder Singh Feryal M. P. Behbahani AI4TS 84 80 0 07 Mar 2023