Advances in gradient echo myelin water imaging at 3T and 7T. - Hyeong-Geol Shin; Se-Hong Oh 001; Masaki Fukunaga; Yoonho Nam; Doo-Hee Lee; Woojin Jung; Minju Jo; Sooyeon Ji; Joon Yul Choi; Jongho Lee 003 (NeuroImage, 2019)

LightMove: A Lightweight Next-POI Recommendation forTaxicab Rooftop Advertising. - Jinsung Jeon; Soyoung Kang; Minju Jo; Seunghyeon Cho; Noseong Park; Seonghoon Kim; Chiyoung Song (CIKM, 2021)

Attentive Neural Controlled Differential Equations for Time-series Classification and Forecasting. - Sheo Yon Jhin; Heejoo Shin; Seoyoung Hong 001; Minju Jo; Solhee Park; Noseong Park; Seungbeom Lee; Hwiyoung Maeng; Seungmin Jeon (ICDM, 2021)

ACE-NODE: Attentive Co-Evolving Neural Ordinary Differential Equations. - Sheo Yon Jhin; Minju Jo; Taeyong Kong; Jinsung Jeon; Noseong Park (KDD, 2021)

LightMove: A Lightweight Next-POI Recommendation for Taxicab Rooftop Advertising. - Jinsung Jeon; Soyoung Kang; Minju Jo; Seunghyeon Cho; Noseong Park; Seonghoon Kim; Chiyoung Song (CoRR, 2021)

TimeKit: A Time-series Forecasting-based Upgrade Kit for Collaborative Filtering. - Seoyoung Hong 001; Minju Jo; Seungji Kook; Jaeeun Jung; Hyowon Wi; Noseong Park; Sung-Bae Cho (IEEE Big Data, 2022)

LORD: Lower-Dimensional Embedding of Log-Signature in Neural Rough Differential Equations. - Jaehoon Lee 002; Jinsung Jeon; Sheo Yon Jhin; Jihyeon Hyeong; Jayoung Kim 002; Minju Jo; Seungji Kook; Noseong Park (ICLR, 2022)

EXIT: Extrapolation and Interpolation-based Neural Controlled Differential Equations for Time-series Classification and Forecasting. - Sheo Yon Jhin; Jaehoon Lee 002; Minju Jo; Seungji Kook; Jinsung Jeon; Jihyeon Hyeong; Jayoung Kim 002; Noseong Park (WWW, 2022)

Learnable Path in Neural Controlled Differential Equations. - Sheo Yon Jhin; Minju Jo; Seungji Kook; Noseong Park (AAAI, 2023)

Hawkes Process Based on Controlled Differential Equations. - Minju Jo; Seungji Kook; Noseong Park (IJCAI, 2023)

Learnable Path in Neural Controlled Differential Equations. - Sheo Yon Jhin; Minju Jo; Seungji Kook; Noseong Park; Sungpil Woo; Sunhwan Lim (CoRR, 2023)

Parameterized Physics-informed Neural Networks for Parameterized PDEs. - Woojin Cho; Minju Jo; Haksoo Lim; Kookjin Lee; Dongeun Lee 001; Sanghyun Hong 001; Noseong Park (ICML, 2024)

Attentive neural controlled differential equations for time-series classification and forecasting. - Sheo Yon Jhin; Heejoo Shin; Sujie Kim; Seoyoung Hong 001; Minju Jo; Solhee Park; Noseong Park; Seungbeom Lee; Hwiyoung Maeng; Seungmin Jeon (Knowl. Inf. Syst., 2024)

Neural Functions for Learning Periodic Signal. - Woojin Cho; Minju Jo; Kookjin Lee; Noseong Park (ICLR, 2025)

Unveiling the Potential of Superexpressive Networks in Implicit Neural Representations. - Uvini Balasuriya Mudiyanselage; Woojin Cho; Minju Jo; Noseong Park; Kookjin Lee (CoRR, 2025)

PDEfuncta: Spectrally-Aware Neural Representation for PDE Solution Modeling. - Minju Jo; Woojin Cho; Uvini Balasuriya Mudiyanselage; Seungjun Lee; Noseong Park; Kookjin Lee (CoRR, 2025)