Smooth Function Approximation by Deep Neural Networks with General Activation Functions. - Ilsang Ohn; Yongdai Kim (Entropy, 2019)

Fast convergence rates of deep neural networks for classification. - Yongdai Kim; Ilsang Ohn; Dongha Kim (Neural Networks, 2021)

Learning fair representation with a parametric integral probability metric. - Dongha Kim; Kunwoong Kim; Insung Kong; Ilsang Ohn; Yongdai Kim (ICML, 2022)

The convergent Indian buffet process. - Ilsang Ohn (CoRR, 2022)

Nonconvex Sparse Regularization for Deep Neural Networks and Its Optimality. - Ilsang Ohn; Yongdai Kim (Neural Comput., 2022)

SLIDE: A surrogate fairness constraint to ensure fairness consistency. - Kunwoong Kim; Ilsang Ohn; Sara Kim; Yongdai Kim (Neural Networks, 2022)

Masked Bayesian Neural Networks : Theoretical Guarantee and its Posterior Inference. - Insung Kong; Dongyoon Yang; Jongjin Lee; Ilsang Ohn; Gyuseung Baek; Yongdai Kim (ICML, 2023)

Intrinsic and extrinsic deep learning on manifolds. - Yihao Fang; Ilsang Ohn; Vijay Gupta 001; Lizhen Lin (CoRR, 2023)

A Bayesian sparse factor model with adaptive posterior concentration. - Ilsang Ohn; Lizhen Lin; Yongdai Kim (CoRR, 2023)

IOFM: Using the Interpolation Technique on the Over-Fitted Models to Identify Clean-Annotated Samples. - Dongha Kim; Yongchan Choi; Kunwoong Kim; Ilsang Ohn; Yongdai Kim (AAAI, 2024)