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Yongchan Kwon
Yongchan Kwon
Columbia University
Verifisert e-postadresse på columbia.edu - Startside
Tittel
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Uncertainty quantification using Bayesian neural networks in classification: Application to biomedical image segmentation
Y Kwon, JH Won, BJ Kim, MC Paik
Computational Statistics & Data Analysis 142, 106816, 2020
528*2020
Mind the gap: Understanding the modality gap in multi-modal contrastive representation learning
W Liang, Y Zhang, Y Kwon, S Yeung, J Zou
Thirty-sixth Conference on Neural Information Processing Systems (NeurIPS 2022), 2022
3942022
ISLES 2016 and 2017-benchmarking ischemic stroke lesion outcome prediction based on multispectral MRI
S Winzeck, A Hakim, R McKinley, JA Pinto, V Alves, C Silva, M Pisov, ...
Frontiers in neurology 9, 679, 2018
1782018
A Bayesian graph convolutional network for reliable prediction of molecular properties with uncertainty quantification
S Ryu, Y Kwon, WY Kim
Chemical science 10 (36), 8438-8446, 2019
167*2019
Beta shapley: a unified and noise-reduced data valuation framework for machine learning
Y Kwon, J Zou
International Conference on Artificial Intelligence and Statistics, 8780-8802, 2022
1502022
Efficient computation and analysis of distributional Shapley values
Y Kwon, MA Rivas, J Zou
International Conference on Artificial Intelligence and Statistics, 793-801, 2021
762021
Ensemble of deep convolutional neural networks for prognosis of ischemic stroke
Y Choi, Y Kwon, H Lee, BJ Kim, MC Paik, JH Won
International Workshop on Brainlesion: Glioma, Multiple Sclerosis, Stroke …, 2017
652017
Datainf: Efficiently estimating data influence in lora-tuned llms and diffusion models
Y Kwon, E Wu, K Wu, J Zou
arXiv preprint arXiv:2310.00902, 2023
542023
WeightedSHAP: analyzing and improving Shapley based feature attributions
Y Kwon, J Zou
Thirty-sixth Conference on Neural Information Processing Systems (NeurIPS 2022), 2022
412022
Data-OOB: Out-of-bag Estimate as a Simple and Efficient Data Value
Y Kwon, J Zou
International Conference on Machine Learning (ICML), 2023
382023
Opendataval: a unified benchmark for data valuation
K Jiang, W Liang, JY Zou, Y Kwon
Advances in Neural Information Processing Systems 36, 2023
352023
Comprehensive Study on Molecular Supervised Learning with Graph Neural Networks
D Hwang, S Yang, Y Kwon, KH Lee, G Lee, H Jo, S Yoon, S Ryu
Journal of Chemical Information and Modeling, 2020
302020
Competing AI: How does competition feedback affect machine learning
A Ginart, E Zhang, Y Kwon, J Zou
International Conference on Artificial Intelligence and Statistics 130, 1693 …, 2021
202021
Valid oversampling schemes to handle imbalance
Y Kim, Y Kwon, MC Paik
Pattern Recognition Letters 125, 661-667, 2019
202019
Calibrated propensity score method for survey nonresponse in cluster sampling
JK Kim, Y Kwon, MC Paik
Biometrika 103 (2), 461-473, 2016
182016
Lipschitz continuous autoencoders in application to anomaly detection
Y Kim, Y Kwon, H Chang, MC Paik
International Conference on Artificial Intelligence and Statistics, 2507-2517, 2020
152020
Data acquisition: A new frontier in data-centric AI
L Chen, B Acun, N Ardalani, Y Sun, F Kang, H Lyu, Y Kwon, R Jia, CJ Wu, ...
arXiv preprint arXiv:2311.13712, 2023
142023
Principled Learning Method for Wasserstein Distributionally Robust Optimization with Local Perturbations
Y Kwon, W Kim, JH Won, MC Paik
International Conference on Machine Learning 119, 5567-5576, 2020
142020
Principled analytic classifier for positive-unlabeled learning via weighted integral probability metric
Y Kwon, W Kim, M Sugiyama, MC Paik
Machine Learning, 1-20, 2019
112019
Generalized estimating equations with stabilized working correlation structure
Y Kwon, YG Choi, T Park, A Ziegler, MC Paik
Computational Statistics & Data Analysis 106, 1-11, 2017
112017
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Artikler 1–20