Deep recurrent spatio-temporal neural network for motor imagery based BCI. - Wonjun Ko; Jee Seok Yoon; Eunsong Kang; Eunji Jun; Jun-Sik Choi; Heung-Il Suk (BCI, 2018)

Domain Adaptation with Source Selection for Motor-Imagery based BCI. - Eunjin Jeon; Wonjun Ko; Heung-Il Suk (BCI, 2019)

Semi-Supervised Deep Adversarial Learning for Brain-Computer Interface. - Wonjun Ko; Eunjin Jeon; Jiyeon Lee; Heung-Il Suk (BCI, 2019)

Plug-in Factorization for Latent Representation Disentanglement. - Jee Seok Yoon; Wonjun Ko; Heung-Il Suk (CoRR, 2019)

Toward Subject Invariant and Class Disentangled Representation in BCI via Cross-Domain Mutual Information Estimator. - Eunjin Jeon; Wonjun Ko; Jee Seok Yoon; Heung-Il Suk (CoRR, 2019)

VIGNet: A Deep Convolutional Neural Network for EEG-based Driver Vigilance Estimation. - Wonjun Ko; Kwanseok Oh; Eunjin Jeon; Heung-Il Suk (BCI, 2020)

Spectro-Spatio-Temporal EEG Representation Learning for Imagined Speech Recognition. - Wonjun Ko; Eunjin Jeon; Heung-Il Suk (ACPR (2), 2021)

Fine-grained Temporal Attention Network for EEG-based Seizure Detection. - Seungwoo Jeong; Eunjin Jeon; Wonjun Ko; Heung-Il Suk (BCI, 2021)

ENGINE: Enhancing Neuroimaging and Genetic Information by Neural Embedding. - Wonjun Ko; Wonsik Jung; Eunjin Jeon; Ahmad Wisnu Mulyadi; Heung-Il Suk (ICDM, 2021)

Multi-Scale Neural Network for EEG Representation Learning in BCI. - Wonjun Ko; Eunjin Jeon; Seungwoo Jeong; Heung-Il Suk (IEEE Comput. Intell. Mag., 2021)

Efficient Continuous Manifold Learning for Time Series Modeling. - Seungwoo Jeong; Wonjun Ko; Ahmad Wisnu Mulyadi; Heung-Il Suk (CoRR, 2021)

A unified framework for personalized regions selection and functional relation modeling for early MCI identification. - Jiyeon Lee; Wonjun Ko; Eunsong Kang; Heung-Il Suk; Alzheimer's Disease Neuroimaging Initiative (NeuroImage, 2021)

Electrophysiological Decoding of Spatial and Color Processing in Human Prefrontal Cortex. - Byoung-Kyong Min; Hyun Seok Kim; Wonjun Ko; Min-Hee Ahn; Heung-Il Suk; Dimitrios Pantazis; Robert T. Knight (NeuroImage, 2021)

Continuous Riemannian Geometric Learning for Sleep Staging Classification. - Seungwoo Jeong; Wonjun Ko; Ahmad Wisnu Mulyadi; Heung-Il Suk (BCI, 2022)

EEG-Oriented Self-Supervised Learning and Cluster-Aware Adaptation. - Wonjun Ko; Heung-Il Suk (CIKM, 2022)

Enhancing Contextual Encoding With Stage-Confusion and Stage-Transition Estimation for EEG-Based Sleep Staging. - Jaeun Phyo; Wonjun Ko; Eunjin Jeon; Heung-Il Suk (ICASSP, 2022)

A Novel RL-Assisted Deep Learning Framework for Task-Informative Signals Selection and Classification for Spontaneous BCIs. - Wonjun Ko; Eunjin Jeon; Heung-Il Suk (IEEE Trans. Ind. Informatics, 2022)

A Deep Generative-Discriminative Learning for Multimodal Representation in Imaging Genetics. - Wonjun Ko; Wonsik Jung; Eunjin Jeon; Heung-Il Suk (IEEE Trans. Medical Imaging, 2022)

TransSleep: Transitioning-Aware Attention-Based Deep Neural Network for Sleep Staging. - Jaeun Phyo; Wonjun Ko; Eunjin Jeon; Heung-Il Suk (IEEE Trans. Cybern., 2023)

Mutual Information-Driven Subject-Invariant and Class-Relevant Deep Representation Learning in BCI. - Eunjin Jeon; Wonjun Ko; Jee Seok Yoon; Heung-Il Suk (IEEE Trans. Neural Networks Learn. Syst., 2023)

Deep Efficient Continuous Manifold Learning for Time Series Modeling. - Seungwoo Jeong; Wonjun Ko; Ahmad Wisnu Mulyadi; Heung-Il Suk (IEEE Trans. Pattern Anal. Mach. Intell., 2024)

EEG-Oriented Self-Supervised Learning With Triple Information Pathways Network. - Wonjun Ko; Seungwoo Jeong; Sa-Kwang Song; Heung-Il Suk (IEEE Trans. Cybern., 2024)

SLEEP-SAFE: Self-Supervised Learning for Estimating Electroencephalogram Patterns With Structural Analysis of Fatigue Evidence. - Wonjun Ko; Jeongwon Choe; Jonggu Kang (IEEE Access, 2025)