Minseop Park
Minseop Park
Qualcomm Korea
Verified email at
Cited by
Cited by
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
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
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, 1-10, 2019
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
Quadapter: Adapter for gpt-2 quantization
M Park, J You, M Nagel, S Chang
arXiv preprint arXiv:2211.16912, 2022
Classifying heart conditions based on class probability output networks
HB Bae, MS Park, RM Kil, HY Youn
Neurocomputing 360, 198-208, 2019
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
Taeml: Task-adaptive ensemble of meta-learners
M Park, S Kim, J Kim, Y Liu, S Choi
NeurIPS 2018 Workshop on Meta-learning, 2018
The system can't perform the operation now. Try again later.
Articles 1–8