Valid oversampling schemes to handle imbalance Y Kim, Y Kwon, MC Paik Pattern Recognition Letters 125, 661-667, 2019 | 15 | 2019 |
Lipschitz Continuous Autoencoders in Application to Anomaly Detection Y Kim, Y Kwon, H Chang, MC Paik International Conference on Artificial Intelligence and Statistics, August 2020, 2020 | 10 | 2020 |
Conditional Wasserstein Generator Y Kim, K Lee, MC Paik IEEE Transactions on Pattern Analysis and Machine Intelligence, 1-12, 2022 | 4 | 2022 |
Explaining Deep Learning-Based Representations of Resting State Functional Connectivity Data: Focusing on Interpreting Nonlinear Patterns in Autism Spectrum Disorder Y Kim, O Ravid, X Zheng, Y Kim, Y Neria, S Lee, X He, X Zhu Frontiers in Psychiatry, 2024 | 1 | 2024 |
Covariate-informed Representation Learning to Prevent Posterior Collapse of iVAE Y Kim, Y Liu, X Wei International Conference on Artificial Intelligence and Statistics 206, 2641 …, 2023 | 1 | 2023 |
Optimizing Contingency Management with Reinforcement Learning Y Kim, L Brandt, K Cheung, EV Nunes, J Roll, SX Luo, Y Liu https://www.medrxiv.org/content/10.1101/2024.03.28.24305031v1, 2024 | | 2024 |
Temporal Generative Models for Learning Heterogeneous Group Dynamics of Ecological Momentary Data S Kim, Y Kim, Y Wang https://www.biorxiv.org/content/10.1101/2023.09.13.557652v1, 2023 | | 2023 |
Wasserstein Geodesic Generator for Conditional Distributions Y Kim, K Lee, Y Choi, JH Won, MC Paik arXiv preprint arXiv:2308.10145, 2023 | | 2023 |
Method and apparatus for conditional data generation using conditional Wasserstein generator MC Paik, Y Kim, K Lee https://doi.org/10.8080/1020210105611, 2023 | | 2023 |
Learning method and learning device for high-dimension unsupervised anomaly detection using kernalized wasserstein autoencoder to lessen too many computations of christophel … MC Paik, Y Kim, H Chang https://patents.google.com/patent/KR102202842B1/en, 2021 | | 2021 |
Statistical distance of conditional distributions and its applications Y Kim Department of Statistics, Seoul National University, 2021 | | 2021 |
Kernel-convoluted Deep Neural Networks with Data Augmentation M Kim, Y Kim, D Kim, Y Kim, MC Paik The Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021 | | 2021 |