JET is a conditional flow matching framework that generates EEG as continuous raw sequences with added constraints for spectral and temporal properties, achieving over 40% lower TS-FID than prior discrete denoising methods on three benchmarks.
arXiv preprint arXiv:2504.11936 , year=
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A multimodal pipeline decodes EEG into 3D meshes via EEG-to-image, MLLM reasoning, diffusion, and single-image-to-3D conversion, reporting 85.4% 10-way accuracy and 0.648 CLIPScore.
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Let EEG Models Learn EEG
JET is a conditional flow matching framework that generates EEG as continuous raw sequences with added constraints for spectral and temporal properties, achieving over 40% lower TS-FID than prior discrete denoising methods on three benchmarks.
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Brain3D: EEG-to-3D Decoding of Visual Representations via Multimodal Reasoning
A multimodal pipeline decodes EEG into 3D meshes via EEG-to-image, MLLM reasoning, diffusion, and single-image-to-3D conversion, reporting 85.4% 10-way accuracy and 0.648 CLIPScore.