6 papers
DIVER-1: Scaling Intracranial EEG Foundation Models for Transferable Representations
Danny Dongyeop Han, Yonghyeon Gwon, Ahhyun Lucy Lee +10
Intracranial EEG (iEEG) provides direct, millisecond-scale recordings of human neural activity, but reusable representation learning is difficult because electrode layouts, anatomi…
Latent-Space Causal Discovery from Indirect Neuroimaging Observations
Sangyoon Bae, Miruna Oprescu, David Keetae Park +2
Neuroimaging does not observe causal variables directly: hemodynamics and volume conduction distort signals so that statistical dependence need not reflect latent neural influence.…
DANCE: Doubly Adaptive Neighborhood Conformal Estimation
Brandon R. Feng, Brian J. Reich, Daniel Beaglehole +7
The recent developments of complex deep learning models have led to unprecedented ability to accurately predict across multiple data representation types. Conformal prediction for…
Uncertainty-Calibrated Spatiotemporal Field Diffusion with Sparse Supervision
Kevin Valencia, Xihaier Luo, Shinjae Yoo +1
Physical fields are typically observed only at sparse, time-varying sensor locations, making forecasting and reconstruction ill-posed and uncertainty-critical. We present SOLID, a…
Scalable Diffusion Transformer for Conditional 4D fMRI Synthesis
Jungwoo Seo, David Keetae Park, Shinjae Yoo +1
Generating whole-brain 4D fMRI sequences conditioned on cognitive tasks remains challenging due to the high-dimensional, heterogeneous BOLD dynamics across subjects/acquisitions an…
DIVER-0 : A Fully Channel Equivariant EEG Foundation Model
Danny Dongyeop Han, Ahhyun Lucy Lee, Taeyang Lee +7
Electroencephalography (EEG) is a non-invasive technique widely used in brain-computer interfaces and clinical applications, yet existing EEG foundation models face limitations in…