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ORCIDMingyu Kim 0002
Person information
- affiliation: Korea Advanced Institute of Science and Technology (KAIST), Seoul, Korea
Other persons with the same name
- Mingyu Kim — disambiguation page
- Mingyu Kim 0001
![[0000-0002-2084-3510]](https://dblp.dagstuhl.de/img/orcid-mark.12x12.png "0000-0002-2084-3510")
— Korea University, Seoul, Korea - Mingyu Kim 0003 — Virginia Polytechnic Institute and State University, Blacksburg, VA, USA
- Mingyu Kim 0004 — University of Ulsan College of Medicine, Seoul, Korea
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Journal Articles
- 2023
[j3]Kyeongryeol Go, Mingyu Kim, Seyoung Yun:
Meta-Learning Amidst Heterogeneity and Ambiguity. IEEE Access 11: 1578-1592 (2023)- [j2]Mingyu Kim, Jihwan Oh, Yongsik Lee, Joonkee Kim, Seonghwan Kim, Song Chong, Seyoung Yun:
The StarCraft Multi-Agent Exploration Challenges: Learning Multi-Stage Tasks and Environmental Factors Without Precise Reward Functions. IEEE Access 11: 37854-37868 (2023) - [j1]Mingyu Kim, Jaekyeong Lee, Leechan Choi, Minjoo Choi:
PolarGAN: Creating realistic Arctic sea ice concentration images with user-defined geometric preferences. Eng. Appl. Artif. Intell. 126: 106920 (2023)
Conference and Workshop Papers
- 2024
- [c2]Mingyu Kim, Jun-Seong Kim, Se-Young Yun, Jin-Hwa Kim:
Synergistic Integration of Coordinate Network and Tensorial Feature for Improving Neural Radiance Fields from Sparse Inputs. ICML 2024 - 2022
- [c1]Mingyu Kim, Kyeongryeol Go, Se-Young Yun:
Neural Processes with Stochastic Attention: Paying more attention to the context dataset. ICLR 2022
Informal and Other Publications
- 2024
- [i3]Mingyu Kim, Jun-Seong Kim, Se-Young Yun, Jin-Hwa Kim:
Synergistic Integration of Coordinate Network and Tensorial Feature for Improving Neural Radiance Fields from Sparse Inputs. CoRR abs/2405.07857 (2024) - 2022
- [i2]Mingyu Kim, Kyeongryeol Go, Se-Young Yun:
Neural Processes with Stochastic Attention: Paying more attention to the context dataset. CoRR abs/2204.05449 (2022) - [i1]Mingyu Kim, Jihwan Oh, Yongsik Lee, Joonkee Kim, Seonghwan Kim, Song Chong, Se-Young Yun:
The StarCraft Multi-Agent Challenges+ : Learning of Multi-Stage Tasks and Environmental Factors without Precise Reward Functions. CoRR abs/2207.02007 (2022)
Coauthor Index
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