Kong, Insung

8 publications

TMLR 2025 Fairness Through Matching Kunwoong Kim, Insung Kong, Jongjin Lee, Minwoo Chae, Sangchul Park, Yongdai Kim

JMLR 2025 Posterior Concentrations of Fully-Connected Bayesian Neural Networks with General Priors on the Weights Insung Kong, Yongdai Kim

ICML 2025 Tensor Product Neural Networks for Functional ANOVA Model Seokhun Park, Insung Kong, Yongchan Choi, Chanmoo Park, Yongdai Kim

ICML 2023 Covariate Balancing Using the Integral Probability Metric for Causal Inference Insung Kong, Yuha Park, Joonhyuk Jung, Kwonsang Lee, Yongdai Kim

ICCV 2023 Enhancing Adversarial Robustness in Low-Label Regime via Adaptively Weighted Regularization and Knowledge Distillation Dongyoon Yang, Insung Kong, Yongdai Kim

ICML 2023 Improving Adversarial Robustness by Putting More Regularizations on Less Robust Samples Dongyoon Yang, Insung Kong, Yongdai Kim

ICML 2023 Masked Bayesian Neural Networks : Theoretical Guarantee and Its Posterior Inference Insung Kong, Dongyoon Yang, Jongjin Lee, Ilsang Ohn, Gyuseung Baek, Yongdai Kim

ICML 2022 Learning Fair Representation with a Parametric Integral Probability Metric Dongha Kim, Kunwoong Kim, Insung Kong, Ilsang Ohn, Yongdai Kim