5 citations · 11 across the 5 of their papers we have counts for
5 papers
Stochastic Optimal Control for Continuous-Time fMRI Representation Learning
Joonhyeong Park, Byoungwoo Park, Chang-Bae Bang +4
Learning robust representations from functional magnetic resonance imaging (fMRI) is fundamentally challenged by the temporal irregularity and noise inherent in data from heterogen…
Cost-Sensitive Multi-Fidelity Bayesian Optimization with Transfer of Learning Curve Extrapolation
Dong Bok Lee, Aoxuan Silvia Zhang, Byungjoo Kim +4
In this paper, we address the problem of cost-sensitive multi-fidelity Bayesian Optimization (BO) for efficient hyperparameter optimization (HPO). Specifically, we assume a scenari…
Joint-Embedding Masked Autoencoder for Self-supervised Learning of Dynamic Functional Connectivity from the Human Brain
Jungwon Choi, Hyungi Lee, Byung-Hoon Kim +1
Graph Neural Networks (GNNs) have shown promise in learning dynamic functional connectivity for distinguishing phenotypes from human brain networks. However, obtaining extensive la…
Large-scale Graph Representation Learning of Dynamic Brain Connectome with Transformers
Byung-Hoon Kim, Jungwon Choi, EungGu Yun +3
Graph Transformers have recently been successful in various graph representation learning tasks, providing a number of advantages over message-passing Graph Neural Networks. Utiliz…
A Generative Self-Supervised Framework using Functional Connectivity in fMRI Data
Jungwon Choi, Seongho Keum, EungGu Yun +2
Deep neural networks trained on Functional Connectivity (FC) networks extracted from functional Magnetic Resonance Imaging (fMRI) data have gained popularity due to the increasing…