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Amin Darabi

Doctorat - UdeM
Superviseur⋅e principal⋅e
Irina Rish
Sujets de recherche
Apprentissage profond

Publications

Introducing Brain Foundation Models
Mohammad Javad Darvishi Bayazi
Hena Ghonia
Roland Riachi
Bruno Aristimunha
Arian Khorasani
Md Rifat Arefin
Sylvain Chevallier
Amin Darabi
Guillaume Dumas
Irina Rish
Brain function represents one of the most complex systems driving our world. Decoding its signals poses significant challenges, particularly… (voir plus) due to the limited availability of data and the high cost of recordings. The existence of large hospital datasets and laboratory collections partially mitigates this issue. However, the lack of standardized recording protocols, varying numbers of channels, diverse setups, scenarios, and recording devices further complicate the task. This work addresses these challenges by introducing the Brain Foundation Model (BFM), a suite of open-source models trained on brain signals. These models serve as foundational tools for various types of time-series neuroimaging tasks. This work presents the first model of the BFM series, which is trained on electroencephalogram signal data. Our results demonstrate that BFM-EEG can generate signals more accurately than other models. Upon acceptance, we will release the model weights and pipeline.
2024-10-10
NeurIPS.cc/2024/Workshop/TSALM (publié)
openreview.net
openreview.net