EEGMamba
importedsoftware/eegmamba
[Neural Networks 2025] EEGMamba: An EEG Foundation Model with Mamba
Machine-generated from the listed sources and not yet reviewed by a human.
- Category
- Software & Systems
- Subcategory
- unknown
- License
- MIT(osi)
- Status
- maintained
- Maturity
- deployed
- Organization
- unknown
- Country
- unknown
- Repository
- github.com/wjq-learning/EEGMamba
- Documentation
- unknown
- Tags
- deep-learning · eeg · eeg-signals · foundation-models · mamba-state-space-models · pretrained-models
- Regulatory
- unknown
Top contributors by commit count, from the project’s public repository. Avatars are served by their origin, not stored here. To be removed from this list, open an issue.
Computed from shared tags, weighted so a rare tag counts for more than a common one. These are suggestions, not curated relationships.
- Large-Scale-Medicalfoundation-models · pretrained-models
[TPAMI 2026] Large-Scale 3D Medical Image Pre-training with Geometric Context Priors
- CBraModeeg · pretrained-models
[ICLR 2025] CBraMod: A Criss-Cross Brain Foundation Model for EEG Decoding
- STU-Netfoundation-models · pretrained-models
The largest pre-trained medical image segmentation model (1.4B parameters) based on the largest public dataset (>100k annotations), up until April 2023.
- STU-Netfoundation-models · pretrained-models
The largest pre-trained medical image segmentation model (1.4B parameters) based on the largest public dataset (>100k annotations) to date.
- LoBrAFramemamba-state-space-models
Unified framework and Mamba for fNIRS: A Unified fNIRS Classification Framework Informed by Local Brain Activation Patterns
- MambaMIMmamba-state-space-models
[MedIA 2025] MambaMIM: Pre-training Mamba with State Space Token Interpolation and its Application to Medical Image Segmentation
- api.github.com/repos/wjq-learning/EEGMambaretrieved 2026-08-05 · via github-api
Machine-imported from GitHub search. Last push 2025-11-17, 99 stars, license reported as MIT. Category and schematic were assigned by keyword heuristics and are unreviewed.
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