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Awesome-Mamba
Awesome list of papers that extend Mamba to various applications.
https://github.com/pengzhangzhi/Awesome-Mamba
Last synced: 2 days ago
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Mamba
- Mamba - space model architecture showing promising performance on language modeling with O(N) complexity.
- mamba.py 🐍 : a simple and efficient Mamba implementation
- Mamba-jax
- Mamba-minimal-pytorch
- Mamba-minimal-in-JAX
- Mamba.c: inference of Mamba models in C and CUDA
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Computer Vision
- Efficient Visual Representation Learning with Bidirectional State Space Model
- MambaMorph: a Mamba-based Backbone with Contrastive Feature Learning for Deformable MR-CT Registration
- Vivim: a Video Vision Mamba for Medical Video Object Segmentation
- SegMamba: Long-range Sequential Modeling Mamba For 3D Medical Image Segmentation
- VMamba: Visual State Space Model
- U-Mamba: Enhancing Long-range Dependency for Biomedical Image Segmentation
- Swin-UMamba
- VM-UNet
- ExpoMamba - FoMo II)
- DiM: Diffusion Mamba for Efficient High-Resolution Image Synthesis - DiffusionMamba)]
- PlainMamba: Improving Non-Hierarchical Mamba in Visual Recognition
- ZigMa (ECCV 2024)
- I2I-Mamba: Multi-modal Medical Image Synthesis via Selective State Space Modeling - lab/I2I-Mamba)]
- SUM: Saliency Unification through Mamba for Visual Attention Modeling
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NLP
- MambaByte: Token-free Selective State Space Model
- Repeat After Me: Transformers are Better than State Space Models at Copying
- Can Mamba Learn How to Learn? A Comparative Study on In-Context Learning Tasks
- MoE-Mamba: Efficient Selective State Space Models with Mixture of Experts
- BlackMamba: Mixture of Experts for State-Space Models
- ClinicalMamba: A Generative Clinical Language Model on Longitudinal Clinical Notes
- Repeat After Me: Transformers are Better than State Space Models at Copying
- Can Mamba Learn How to Learn? A Comparative Study on In-Context Learning Tasks
- LOCOST: State-Space Models for Long Document Abstractive Summarization
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Graph
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Medical
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Theory
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Acknowledgement
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