Scale Mixtures of Neural Network Gaussian Processes. - Hyungi Lee; Eunggu Yun 001; Hongseok Yang; Juho Lee 001 (ICLR, 2022)

Martingale Posterior Neural Processes. - Hyungi Lee; Eunggu Yun 001; Giung Nam; Edwin Fong; Juho Lee 001 (ICLR, 2023)

Probabilistic Imputation for Time-series Classification with Missing Data. - Seunghyun Kim; Hyunsu Kim; Eunggu Yun 001; Hwangrae Lee; Jaehun Lee; Juho Lee 001 (ICML, 2023)

Traversing Between Modes in Function Space for Fast Ensembling. - Eunggu Yun 001; Hyungi Lee; Giung Nam; Juho Lee 001 (ICML, 2023)

A Generative Self-Supervised Framework using Functional Connectivity in fMRI Data. - Jungwon Choi; Seongho Keum; Eunggu Yun 001; Byung-Hoon Kim; Juho Lee 001 (CoRR, 2023)

Large-scale Graph Representation Learning of Dynamic Brain Connectome with Transformers. - Byung-Hoon Kim; Jungwon Choi; Eunggu Yun 001; Kyungsang Kim; Xiang Li 001; Juho Lee 001 (CoRR, 2023)

A Simple Early Exiting Framework for Accelerated Sampling in Diffusion Models. - Tae Hong Moon; Moonseok Choi; EungGu Yun 001; Jongmin Yoon; Gayoung Lee; Jaewoong Cho; Juho Lee 001 (ICML, 2024)

Learning Dynamic Brain Connectome with Graph Transformers for Psychiatric Diagnosis Classification. - Byung-Hoon Kim; Jungwon Choi; EungGu Yun 001; Kyungsang Kim; Xiang Li 001; Juho Lee 001 (ISBI, 2024)

On-Off Pattern Encoding and Path-Count Encoding as Deep Neural Network Representations. - Euna Jung; Jaekeol Choi; EungGu Yun 001; Wonjong Rhee (CoRR, 2024)

Language-Assisted Feature Transformation for Anomaly Detection. - EungGu Yun 001; Heonjin Ha; Yeongwoo Nam; Bryan Dongik Lee (ICLR, 2025)