是的!这就是 Mamba 提供的功能,但在深入了解其架构之前,让我们首先来看看State Space Models. 第三部分,什么是State Space Model 还是先看看什么是State Space(状态空间) 状态空间包含完整描述系统的最小数量的变量。它是一种通过定义系统的可能状态来以数学方式表示问题的方法。 想象你在一个迷宫里,目标是从起点...
Section 2 State Space Models 状态空间模型 结构化状态空间序列模型(Structured state space sequence models,S4)是最近一类用于深度学习的序列模型,与 RNN、CNN 和经典状态空间模型广泛相关。它们受到一个特定连续系统 (1) 的启发,该系统通过一个隐含的潜在状态 h(t)∈RNh(t)∈RN 映射一个一维函数或序列 x(t...
Mamba模型中，"A"、"B"、"C"和"D"分别代表状态空间模型（State Space Models，简称SSMs）的参数。这...
论文:Simplified State Space Layers for Sequence Modeling 要点:将多入多出状态空间模型引入 S4 层并将其与高效的并行扫描相结合,提出了新的 S5 层。 H3-attention language model 论文:Hungry Hungry Hippos: Towards Language Modeling with State Space Models 要点:设计了一个新的 SSM 层 H3,几乎填平了 SSM ...
A Visual Guide to Mamba and State Space Models 一文通透想颠覆Transformer的Mamba:从SSM、S4到mamba、线性transformer(含RWKV解析)_mamba模型-CSDN博客 sonta:[线性RNN系列] Mamba: S4史诗级升级 《Mamba: Linear-Time Sequence Modeling with Selective State Spaces》阅读笔记 看图学:大模型推理加速:看图学KV Cac...
State Space Models (SSMs) have emerged as promising alternatives for sequence modeling paradigms, especially with the advent of S4 and its variants, such as S4nd, Hippo, Hyena, Diagonal State Spaces (DSS), Gated State Spaces (GSS), Linear Recurrent Unit (LRU), Liquid-S4, Long-Conv, Mega,...
27 May 2024·Biqing Qi,Junqi Gao,Kaiyan Zhang,Dong Li,Jianxing Liu,Ligang Wu,BoWen Zhou· Despite the promising performance of state space models (SSMs) in long sequence modeling, limitations still exist. Advanced SSMs like S5 and S6 (Mamba) in addressing non-uniform sampling, their recursive...
Paper tables with annotated results for On the Parameterization and Initialization of Diagonal State Space Models
Deep state-space models (DSSMs) enable temporal predictions by learning the underlying dynamics of observed sequence data. They are often trained by maximising the evidence lower bound. However, as we show, this does not ensure the model actually learns the underlying dynamics. We therefore ...
Hungry hungry hippos: Towards language modeling with state space models, 2023. Gu, A., and Dao, T. Mamba: Linear-time sequence modeling with selective state spaces, 2023. Gu, A., Dao, T., Ermon, S., Rudra, A., and Re, C. Hippo: Recurrent memory with optimal polynomial projections,...