References
A curated list of recent research and implementations using Mamba-based state space models.
Mamba-based Models and Applications
- Is Mamba Effective for Time Series Forecasting?
- Paper (arXiv:2403.11144)
- GitHub Repository
- A study of Mamba’s performance on time series forecasting tasks compared to standard models.
- STG-Mamba: Spatial-Temporal Graph Learning via Selective State Space Model
- Paper (arXiv:2403.12418)
- GitHub Repository
- Introduces Mamba for spatial-temporal graph data, effective in traffic and sensor network forecasting.
- Graph Mamba: Towards Learning on Graphs with State Space Models
- Paper (arXiv:2402.08678)
- Explores adapting state space models to graph data, with competitive results on graph classification tasks.
- Graph-Mamba: Towards Long-Range Graph Sequence Modeling with Selective State Spaces
- Paper (arXiv link not listed)
- GitHub Repository
- Focuses on long-range dependencies in graph sequences using selective state space models.
- PointMamba: A Simple State Space Model for Point Cloud Analysis
- Paper (arXiv:2402.10739)
- GitHub Repository
- Applies Mamba architecture to point cloud data for 3D vision tasks.
- ClinicalMamba: A Generative Clinical Language Model on Longitudinal Clinical Notes
- Paper (arXiv:2403.05795)
- GitHub Repository
- Utilizes Mamba to model long-range dependencies in clinical notes for language modeling in healthcare.