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pro vyhledávání: '"Park Sihwan"'
Autor:
Jang, Doohyuk, Park, Sihwan, Yang, June Yong, Jung, Yeonsung, Yun, Jihun, Kundu, Souvik, Kim, Sung-Yub, Yang, Eunho
Auto-Regressive (AR) models have recently gained prominence in image generation, often matching or even surpassing the performance of diffusion models. However, one major limitation of AR models is their sequential nature, which processes tokens one
Externí odkaz:
http://arxiv.org/abs/2410.03355
Explaining generalizations and preventing over-confident predictions are central goals of studies on the loss landscape of neural networks. Flatness, defined as loss invariability on perturbations of a pre-trained solution, is widely accepted as a pr
Externí odkaz:
http://arxiv.org/abs/2209.15208
Publikováno v:
In Journal of Cleaner Production 10 June 2024 457
Publikováno v:
In Journal of Industrial and Engineering Chemistry July 2024
Publikováno v:
In Journal of Cleaner Production 1 January 2024 434
Publikováno v:
In Energy 1 December 2023 284
Autor:
Park, Sihwan1 (AUTHOR) sihwan@pusan.ac.kr, Noh, Wonjun1 (AUTHOR) wonjun@pusan.ac.kr, Park, Jaedeuk2 (AUTHOR) jdpark@krict.re.kr, Park, Jinwoo3 (AUTHOR) jinwoop@kongju.ac.kr, Lee, Inkyu1 (AUTHOR) jinwoop@kongju.ac.kr
Publikováno v:
Energies (19961073). Jul2022, Vol. 15 Issue 13, p4560-N.PAG. 19p.
Akademický článek
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Autor:
Park Sihwan
Publikováno v:
Democratic Legal Studies. :289-329
Autor:
Park Sihwan
Publikováno v:
Kyung Hee Law Journal. 51:557-586