Learning deep generative models based on binomial log-likelihood.

Insung Kong

Hwichang Jeong Insung Kong Yongdai Kim Learning deep generative models based on binomial log-likelihood. 131009 2025 651 Neurocomputing https://doi.org/10.1016/j.neucom.2025.131009 db/journals/ijon/ijon651.html#JeongKK25

Insung Kong Yongdai Kim Posterior Concentrations of Fully-Connected Bayesian Neural Networks with General Priors on the Weights. 94:1-94:60 2025 26 J. Mach. Learn. Res. https://jmlr.org/papers/v26/24-0425.html db/journals/jmlr/jmlr26.html#KongK25

Insung Kong Kunwoong Kim Yongdai Kim Fair Representation Learning for Continuous Sensitive Attributes Using Expectation of Integral Probability Metrics. 3784-3795 2025 May 47 IEEE Trans. Pattern Anal. Mach. Intell. 5 https://doi.org/10.1109/TPAMI.2025.3538915 db/journals/pami/pami47.html#KongKK25 streams/journals/pami

Kunwoong Kim Insung Kong Jongjin Lee Minwoo Chae Sangchul Park Yongdai Kim Fairness Through Matching. 2025 2025 Trans. Mach. Learn. Res. https://openreview.net/forum?id=dHljjaNHh1 db/journals/tmlr/tmlr2025.html#KimKLCPK25

Seokhun Park Insung Kong Yongchan Choi Chanmoo Park Yongdai Kim Tensor Product Neural Networks for Functional ANOVA Model. 2025 ICML https://proceedings.mlr.press/v267/park25d.html https://openreview.net/forum?id=Ci3nWnys6T conf/icml/2025 db/conf/icml/icml2025.html#ParkKCPK25

Kunwoong Kim Insung Kong Jongjin Lee Minwoo Chae Sangchul Park Yongdai Kim Fairness Through Matching. 2025 January abs/2501.02793 CoRR https://doi.org/10.48550/arXiv.2501.02793 db/journals/corr/corr2501.html#abs-2501-02793 streams/journals/corr

Seokhun Park Insung Kong Yongchan Choi Chanmoo Park Yongdai Kim Tensor Product Neural Networks for Functional ANOVA Model. 2025 February abs/2502.15215 CoRR https://doi.org/10.48550/arXiv.2502.15215 db/journals/corr/corr2502.html#abs-2502-15215 streams/journals/corr

Yuha Park Kunwoong Kim Insung Kong Yongdai Kim ReLU integral probability metric and its applications. 2025 April abs/2504.18897 CoRR https://doi.org/10.48550/arXiv.2504.18897 db/journals/corr/corr2504.html#abs-2504-18897 streams/journals/corr

Insung Kong Juntong Chen Sophie Langer Johannes Schmidt-Hieber On the expressivity of deep Heaviside networks. 2025 May abs/2505.00110 CoRR https://doi.org/10.48550/arXiv.2505.00110 db/journals/corr/corr2505.html#abs-2505-00110 streams/journals/corr

Insung Kong Kunwoong Kim Yongdai Kim Fair Representation Learning for Continuous Sensitive Attributes using Expectation of Integral Probability Metrics. 2025 May abs/2505.06435 CoRR https://doi.org/10.48550/arXiv.2505.06435 db/journals/corr/corr2505.html#abs-2505-06435 streams/journals/corr

Seokhun Park Insung Kong Yongdai Kim Bayesian Additive Regression Trees for functional ANOVA model. 2025 September abs/2509.03317 CoRR https://doi.org/10.48550/arXiv.2509.03317 db/journals/corr/corr2509.html#abs-2509-03317 streams/journals/corr

Seokhun Park Choeun Kim Jihu Lee Yunseop Shin Insung Kong Yongdai Kim Bayesian Neural Networks for Functional ANOVA model. 2025 October abs/2510.00545 CoRR https://doi.org/10.48550/arXiv.2510.00545 db/journals/corr/corr2510.html#abs-2510-00545 streams/journals/corr

Shayan Hundrieser Philipp Tuchel Insung Kong Johannes Schmidt-Hieber On the Universal Representation Property of Spiking Neural Networks. 2025 December abs/2512.16872 CoRR https://doi.org/10.48550/arXiv.2512.16872 db/journals/corr/corr2512.html#abs-2512-16872 streams/journals/corr

Insung Kong Yongdai Kim Posterior concentrations of fully-connected Bayesian neural networks with general priors on the weights. 2024 abs/2403.14225 CoRR https://doi.org/10.48550/arXiv.2403.14225 db/journals/corr/corr2403.html#abs-2403-14225

Dongyoon Yang Insung Kong Yongdai Kim Enhancing Adversarial Robustness in Low-Label Regime via Adaptively Weighted Regularization and Knowledge Distillation. 4529-4538 2023 ICCV https://doi.org/10.1109/ICCV51070.2023.00420 conf/iccv/2023 db/conf/iccv/iccv2023.html#YangKK23 Insung Kong Yuha Park Joonhyuk Jung Kwonsang Lee Yongdai Kim Covariate balancing using the integral probability metric for causal inference. 17430-17461 2023 ICML https://proceedings.mlr.press/v202/kong23d.html conf/icml/2023 db/conf/icml/icml2023.html#KongPJLK23 Insung Kong Dongyoon Yang Jongjin Lee Ilsang Ohn Gyuseung Baek Yongdai Kim Masked Bayesian Neural Networks : Theoretical Guarantee and its Posterior Inference. 17462-17491 2023 ICML https://proceedings.mlr.press/v202/kong23e.html conf/icml/2023 db/conf/icml/icml2023.html#KongYLOBK23 Dongyoon Yang Insung Kong Yongdai Kim Improving Adversarial Robustness by Putting More Regularizations on Less Robust Samples. 39331-39348 2023 ICML https://proceedings.mlr.press/v202/yang23h.html conf/icml/2023 db/conf/icml/icml2023.html#YangKK23

Insung Kong Yuha Park Joonhyuk Jung Kwonsang Lee Yongdai Kim Covariate balancing using the integral probability metric for causal inference. 2023 abs/2305.13715 CoRR https://doi.org/10.48550/arXiv.2305.13715 db/journals/corr/corr2305.html#abs-2305-13715

Insung Kong Dongyoon Yang Jongjin Lee Ilsang Ohn Gyuseung Baek Yongdai Kim Masked Bayesian Neural Networks : Theoretical Guarantee and its Posterior Inference. 2023 abs/2305.14765 CoRR https://doi.org/10.48550/arXiv.2305.14765 db/journals/corr/corr2305.html#abs-2305-14765

Dongyoon Yang Insung Kong Yongdai Kim Enhancing Adversarial Robustness in Low-Label Regime via Adaptively Weighted Regularization and Knowledge Distillation. 2023 abs/2308.04061 CoRR https://doi.org/10.48550/arXiv.2308.04061 db/journals/corr/corr2308.html#abs-2308-04061

Dongha Kim Kunwoong Kim Insung Kong Ilsang Ohn Yongdai Kim Learning fair representation with a parametric integral probability metric. 11074-11101 2022 ICML https://proceedings.mlr.press/v162/kim22b.html conf/icml/2022 db/conf/icml/icml2022.html#KimKKOK22

Dongha Kim Kunwoong Kim Insung Kong Ilsang Ohn Yongdai Kim Learning fair representation with a parametric integral probability metric. 2022 abs/2202.02943 CoRR https://arxiv.org/abs/2202.02943 db/journals/corr/corr2202.html#abs-2202-02943

Dongyoon Yang Insung Kong Yongdai Kim Adaptive Regularization for Adversarial Training. 2022 abs/2206.03353 CoRR https://doi.org/10.48550/arXiv.2206.03353 db/journals/corr/corr2206.html#abs-2206-03353

Gyuseung Baek Minwoo Chae Juntong Chen Yongchan Choi Shayan Hundrieser Hwichang Jeong Joonhyuk Jung Choeun Kim Dongha Kim Kunwoong Kim Yongdai Kim Sophie Langer Jihu Lee Jongjin Lee Kwonsang Lee Ilsang Ohn Chanmoo Park Sangchul Park Seokhun Park Yuha Park Johannes Schmidt-Hieber Yunseop Shin Philipp Tuchel Dongyoon Yang