openmedical/registry
← registry

EEGDiffuser

imported

software/eegdiffuser

[Neurocomputing 2026] EEGDiffuser: Label-guided EEG signals synthesis via diffusion model for BCI applications

Machine-generated from the listed sources and not yet reviewed by a human.

EEGDiffuser project image
GitHub preview card for wjq-learning/EEGDiffuser. Served by its origin, not stored here, and not covered by this registry’s licence.
record
Category
Software & Systems
Subcategory
unknown
License
MIT(osi)
Status
maintained
Maturity
deployed
Organization
unknown
Country
unknown
Documentation
unknown
Tags
diffusion-models · eeg · eeg-signals
Regulatory
unknown
similar by tags

Computed from shared tags, weighted so a rare tag counts for more than a common one. These are suggestions, not curated relationships.

  • nn_project_dreamdiffusiondiffusion-models · eeg

    Re-implementation of the method proposed in ''DreamDiffusion: Generating High-Quality Images from Brain EEG Signals'' by Y. Bai, X. Wang et al. for Neural Network Course exam Topics

  • Athenaeeg · eeg-signals

    ATHENA (Automatic Toolbox for Handling Experimental Neural Analysis)

  • AugmentedBCIFrameworkeeg · eeg-signals

    The UniPA BCI Framework is an Augmented Brain-Computer Interface framework based on the P300 paradigm with further additional modules to perform the acquisition of eye gaze and physiological features.

  • BDF.jleeg · eeg-signals

    Module to read Biosemi BDF files with the Julia programming language

  • bossdevice-api-matlabeeg · eeg-signals

    sync2brain's bossdevice RESEARCH Application Programmable Interface (API) for MATLAB

  • CSP-Pythoneeg · eeg-signals

    Python implementation of the CSP algorithm

sources
  1. api.github.com/repos/wjq-learning/EEGDiffuser
    retrieved 2026-08-25 · via github-api

    Machine-imported from GitHub search. Last push 2026-01-07, 32 stars, license reported as MIT. Category and schematic were assigned by keyword heuristics and are unreviewed.

Not yet verified by a human. Correct this record →

machine-readable

/v1/entries/44.json→ .entries["eegdiffuser"]

Entries are sharded 64 ways by a stable hash of the id, so a consumer can find any record without an index.