11 papers
Image Classification on IBM Quantum Computers
Junghoon Justin Park, Jiook Cha, Jun-gyeong Park +2
Quantum machine learning on real noisy intermediate-scale quantum (NISQ) hardware has remained largely confined to binary or few-class tasks, limited by the cost of on-hardware tra…
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…
PIMSM: Physics-Informed Multi-Scale Mamba for Stable Neural Representations under Distribution Shift
Sangyoon Bae, Shinjae Yoo, Jiook Cha
Scientific foundation models are expected to reuse representations under changes in dataset, acquisition protocol, and deployment domain, yet many sequence backbones treat scientif…
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.…
Decoding Dynamic Visual Experience from Calcium Imaging via Cell-Pattern-Aware Pretraining
Sangyoon Bae, Mehdi Azabou, Blake Richards +1
Neural recordings exhibit a distinctive form of heterogeneity rooted in differences in cell types, intrinsic circuit dynamics, and stochastic stimulus-response variability that goe…
Can Natural Image Autoencoders Compactly Tokenize fMRI Volumes for Long-Range Dynamics Modeling?
Peter Yongho Kim, Juhyeon Park, Jungwoo Park +4
Modeling long-range spatiotemporal dynamics in functional Magnetic Resonance Imaging (fMRI) remains a key challenge due to the high dimensionality of the four-dimensional signals.…