6 papers
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…
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.…
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…
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…