Machine learningDeep Learning, Sequence Models, State Space Models
Mamba（状态空间模型）
Mamba是Gu和Dao于2023年推出的一种序列模型架构，它在保持语言建模任务强大性能的同时，实现了线性时间复杂度。通过将状态空间模型与输入依赖的选择性相结合，Mamba解决了Transformer的二次复杂度问题，同时保留了建模能力。
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来源
- Gu, A., & Dao, C. (2023). Mamba: Linear-time sequence modeling with selective state spaces. arXiv preprint arXiv:2312.08956. link ↗
如何引用本页
ScholarGate. (2026, June 3). Mamba: Linear-Time Sequence Modeling with Selective State Spaces. ScholarGate. https://scholargate.app/zh/deep-learning/mamba
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