Zobrazeno 1 - 10
of 274
pro vyhledávání: '"Kim, Jun‐Hyeong"'
This study introduces a modified score matching method aimed at generating molecular structures with high energy accuracy. The denoising process of score matching or diffusion models mirrors molecular structure optimization, where scores act like phy
Externí odkaz:
http://arxiv.org/abs/2411.19769
Transporting between arbitrary distributions is a fundamental goal in generative modeling. Recently proposed diffusion bridge models provide a potential solution, but they rely on a joint distribution that is difficult to obtain in practice. Furtherm
Externí odkaz:
http://arxiv.org/abs/2410.01500
As quantum chemical properties have a dependence on their geometries, graph neural networks (GNNs) using 3D geometric information have achieved high prediction accuracy in many tasks. However, they often require 3D geometries obtained from high-level
Externí odkaz:
http://arxiv.org/abs/2304.03724
Autor:
Han, Ayeong a, b, Qamar, Ahmad Yar c, Bang, Seonggyu a, b, Kim, Heyyoung a, e, Kang, Heejae a, b, Kim, Jun-Hyeong d, Choi, Kimyung d, Yun, Sung Ho f, Kim, Seung Il f, Saadeldin, Islam M. b, g, Lee, Sanghoon b, Cho, Jongki a, ⁎
Publikováno v:
In Theriogenology 1 March 2025 234:216-224
Publikováno v:
In Applied Thermal Engineering 1 October 2024 254
Autor:
Lee, Yongjin, Shim, Joohyun, Ko, Nayoung, Kim, Hyoung-Joo, Kim, Jun-Hyeong, Kim, Hyunil, Choi, Kimyung
Publikováno v:
In Theriogenology 1 October 2024 227:49-59
Publikováno v:
In eTransportation September 2024 21
Publikováno v:
In Applied Thermal Engineering 1 June 2024 246
Publikováno v:
In Theriogenology 1 April 2024 218:193-199
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