如此,S4的定义就出来了:序列的结构化状态空间——Structured State Space for Sequences,一类可以有效处理长序列的 SSM(S4所对应的论文为:Efficiently Modeling Long Sequences with Structured State Spaces) 参考博客: Albert Gu本人的scratch tuturial 很详细 csdn某大佬总结 论文: S4 HiPPO 本文使用 Zhihu On VSCod...
在S4模型中,作者将几个SSM块堆叠,搭配适当的归一化层和类似Transformer的逐点全连接层,展现了长程依赖中良好的序列分类性能。 S4层参数化了一个保形映射,其形状为 Batch*model dimension*length dimension,因此可以作为transformer,RNN或一维卷积层的drop-inreplacement。在S4的基础上,作者提出了SaShiMi的序列生成模型,...
We propose the Structured State Space sequence model (S4) based on a new parameterization for the SSM, and show that it can be computed much more efficiently than prior approaches while preserving their theoretical strengths. Our technique involves conditioning A with a low-rank correction, ...
We propose the Structured State Space sequence model (S4) based on a new parameterization for the SSM, and show that it can be computed much more efficiently than prior approaches while preserving their theoretical strengths. Our technique involves conditioning \( A \) with a low-rank ...
configs/model/README.md configs/experiment/README.md sashimi/README.md Citation If you use this codebase, or otherwise found our work valuable, please cite: @article{gu2022s4d, title={On the Parameterization and Initialization of Diagonal State Space Models}, author={Gu, Albert and Gupta, ...
In particular, the SSM kernel is particularly sensitive to the (A,B) (and sometimes Δ parameters), so the learning rate on these parameters is sometimes lowered and the weight decay is always set to 0. See the method register in the model (e.g. s4d.py) and the function setup_...
It is worthy of pointing out that the least spatial unit that was considered in this research is the state of residence, which is naturally composed of many geographical compartments. Consequently, within state variability in fertility can be expected, and thus, an analysis that considers smaller ...
这篇文章[1]采用了 conditional diffusion model 来做时间序列的 imputation 以及 forecasting 任务。本文的亮点在于,diffusion model 的网络结构不再是 CSDI[2] 中的transformer 结构,而是 structured state-space model(SSM)。我们可以把这种结构理解为 RNN、一维 CNN 以及 transformer 的平替结构,都是 seq-to-seq ...
This section describes how to use the latest S4 model and reproduce experiments immediately. More detailed descriptions of the infrastructure are in the subsequent sections. Structured State Space (S4) The S4 module is found atsrc/models/sequence/ss/s4.py. ...
In particular, the SSM kernel is particularly sensitive to the (A,B) (and sometimes Δ parameters), so the learning rate on these parameters is sometimes lowered and the weight decay is always set to 0.See the method register in the model (e.g. s4d.py) and the function setup_...