原文地址：https://pub.towardsai.net/understanding-mamba-and-selective-state-space-models-ssms-1519c...
为了解决上面的问题,作者提出了一种新的选择性 SSM(Selective State Space Models,简称 S6 或 Mamba)。这种模型通过让 SSM 的矩阵 A、B、C 依赖于输入数据,从而实现了选择性。这意味着模型可以根据当前的输入动态地调整其状态,选择性地传播或忽略信息。 Mamba 集成了 S4 和 Transformer 的精华,一个更加高效(S4)...
code:https://github.com/state-spaces/mamba/tree/main Selective State Space Models:让SSM的计算和输入相关 Ecient Implementation of Selective SSMs:加速算法计算 A Simplied SSM Architecture:使用提出的算法,构造了一个block Selective State Space Models 为了有选择性的压缩信息,应该让B、C依赖于输入的参数 SSM...
解决方案: 为了解决这一问题,论文提出了一种新的序列模型架构——Mamba(Selective State Space Models, SSMs),它通过以下几个关键改进来提高效率: 选择机制:通过将SSM参数设置为输入的函数,模型能够根据当前的输入选择性地传播或遗忘信息。 硬件感知并行算法:设计了一种新的硬件感知并行算法,通过递归模式(recurrent mod...
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...
In this report, we identify the inability of these models to perform content-based reasoning as a key weakness and focus on Mamba, a novel neural network architecture that integrates selective structured state space models (SSMs) to address this limitation. Links Report Presentation References Fu, ...
subsampling, which falls short in data-dependent context reasoning. State space models (SSMs), such as Mamba, have gained prominence for their effectiveness and efficiency in modeling long-range dependencies in sequential data. However, adapting SSMs to non-sequential graph data presents a notable ...
Within the FER-YOLO-Mamba model, we further devise a FER-YOLO-VSS dual-branch module, which combines the inherent strengths of convolutional layers in local feature extraction with the exceptional capability of State Space Models (SSMs) in revealing long-distance dependencies. To the best of our...
10. The results reveal that our LSKNet-T and LSKNet-S perform exceptionally well, achieving state- of-the-art mAP scores of 46.93% and 47.87% respectively, surpassing all other models by a significant margin. 4.5. Analysis Detection Results Visualization. Visualization e...
Deep state-space models (DSSMs) have gained popularity in recent years due to their potent modeling capacity for dynamic systems. However, existing DSSM wo... Y Zhang,Z Lin,Y Sun,... 被引量: 0发表: 2024年 Bio-inspired, task-free continual learning through activity regularization The abili...