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Young-geun Kim
Young-geun Kim
Postdoc fellow, Department of Biostatistics and Department of Psychiatry, Columbia University
Verified email at nyspi.columbia.edu - Homepage
Title
Cited by
Cited by
Year
Valid oversampling schemes to handle imbalance
Y Kim, Y Kwon, MC Paik
Pattern Recognition Letters 125, 661-667, 2019
152019
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
102020
Conditional Wasserstein Generator
Y Kim, K Lee, MC Paik
IEEE Transactions on Pattern Analysis and Machine Intelligence, 1-12, 2022
42022
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
12024
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
12023
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
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Articles 1–12