HiPPO-Prophecy: State-Space Models can Provably Learn Dynamical Systems in Context

12 July 2024

Papers citing "HiPPO-Prophecy: State-Space Models can Provably Learn Dynamical Systems in Context"

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 45 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 65 0 0 17 Feb 2025
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 61 117 0 29 Feb 2024
How Many Pretraining Tasks Are Needed for In-Context Learning of Linear Regression? Jingfeng Wu Difan Zou Zixiang Chen Vladimir Braverman Quanquan Gu Peter L. Bartlett 131 52 0 12 Oct 2023
Resurrecting Recurrent Neural Networks for Long Sequences Antonio Orvieto Samuel L. Smith Albert Gu Anushan Fernando Çağlar Gülçehre Razvan Pascanu Soham De 88 271 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 97 84 0 07 Mar 2023
How to Train Your HiPPO: State Space Models with Generalized Orthogonal Basis Projections Albert Gu Isys Johnson Aman Timalsina Atri Rudra Christopher Ré Mamba 97 90 0 24 Jun 2022