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Minseop Park
Minseop Park
Qualcomm Korea
Verified email at qti.qualcomm.com
Title
Cited by
Cited by
Year
Learning to propagate labels: Transductive propagation network for few-shot learning
Y Liu, J Lee, M Park, S Kim, E Yang, SJ Hwang, Y Yang
arXiv preprint arXiv:1805.10002, 2018
4962018
Learning to balance: Bayesian meta-learning for imbalanced and out-of-distribution tasks
HB Lee, H Lee, D Na, S Kim, M Park, E Yang, SJ Hwang
arXiv preprint arXiv:1905.12917, 2019
692019
A deep learning model for real-time mortality prediction in critically ill children
SY Kim, S Kim, J Cho, YS Kim, IS Sol, Y Sung, I Cho, M Park, H Jang, ...
Critical care 23 (1), 1-10, 2019
592019
Mxml: Mixture of meta-learners for few-shot classification
M Park, J Kim, S Kim, Y Liu, S Choi
arXiv preprint arXiv:1904.05658, 2019
62019
Classifying heart conditions based on class probability output networks
HB Bae, MS Park, RM Kil, HY Youn
Neurocomputing 360, 198-208, 2019
42019
TAEML: Task-Adaptive Ensemble of Meta-Learners
M Park, S Kim, J Kim, Y Liu, S Choi
NeurIPS 2018 Workshop on Meta-learning, 2018
32018
Method For Predicting Of Mortality Risk Or Sepsis Risk And Device For Predicting Of Mortality Risk Or Sepsis Risk Using The Same
YS Kim, KS Chung, JK Yoo, YC Sung, IH Cho, SH Kim, MS Park
US Patent App. 16/598,096, 2020
22020
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