Simplifying and Understanding State Space Models with Diagonal Linear RNNs

1 December 2022

Papers citing "Simplifying and Understanding State Space Models with Diagonal Linear RNNs"

7 / 7 papers shown

Title
FACTS: A Factored State-Space Framework For World Modelling Li Nanbo Firas Laakom Yucheng Xu Wenyi Wang Jürgen Schmidhuber AI4TS 50 0 0 28 Oct 2024
Hieros: Hierarchical Imagination on Structured State Space Sequence World Models Paul Mattes Rainer Schlosser R. Herbrich 16 4 0 08 Oct 2023
Focus Your Attention (with Adaptive IIR Filters) Shahar Lutati Itamar Zimerman Lior Wolf 24 9 0 24 May 2023
Downstream Datasets Make Surprisingly Good Pretraining Corpora Kundan Krishna Saurabh Garg Jeffrey P. Bigham Zachary Chase Lipton 33 30 0 28 Sep 2022
Mixture-of-Experts with Expert Choice Routing Yan-Quan Zhou Tao Lei Han-Chu Liu Nan Du Yanping Huang Vincent Zhao Andrew M. Dai Zhifeng Chen Quoc V. Le James Laudon MoE 147 323 0 18 Feb 2022
Masked Autoencoders Are Scalable Vision Learners Kaiming He Xinlei Chen Saining Xie Yanghao Li Piotr Dollár Ross B. Girshick ViT TPM 258 7,337 0 11 Nov 2021
Zero-Shot Text-to-Image Generation Aditya A. Ramesh Mikhail Pavlov Gabriel Goh Scott Gray Chelsea Voss Alec Radford Mark Chen Ilya Sutskever VLM 253 4,735 0 24 Feb 2021