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Showing results 1 to 13 of 13

1
2023 Roadmap on molecular modelling of electrochemical energy materials

Zhang, Chao; Cheng, Jun; Chen, Yiming; Chan, Maria K. Y.; Cai, Qiong; Carvalho, Rodrigo P.; Marchiori, Cleber F. N.; et al, JOURNAL OF PHYSICS-ENERGY, v.5, no.4, 2023-10

2
Accelerating Optimal Experimental Design for Robust Synchronization of Uncertain Kuramoto Oscillator Model Using Machine Learning

Woo, Hyun-Myung; Hong, Youngjoon; Kwon, Bongsuk; Yoon, Byung-Jun, IEEE TRANSACTIONS ON SIGNAL PROCESSING, v.69, pp.6473 - 6487, 2021

3
Bimetallic Gold-Silver Nanostructures Drive Low Overpotentials for Electrochemical Carbon Dioxide Reduction

Park, Joon Woo; Choi, Woong; Noh, Juhwan; Park, Woonghyeon; Gu, Geun Ho; Park, Jonghyeok; Jung, Yousung; et al, ACS APPLIED MATERIALS & INTERFACES, v.14, no.5, pp.6604 - 6614, 2022-02

4
Enhanced Deep-Learning Prediction of Molecular Properties via Augmentation of Bond Topology

Cho, Hyeoncheol; Choi, Insung S., CHEMMEDCHEM, v.14, no.17, pp.1604 - 1609, 2019-09

5
Feasibility of Activation Energy Prediction of Gas-Phase Reactions by Machine Learning

Choi, Sunghwan; Kim, Yeonjoon; Kim, Jin Woo; Kim, Zeehyo; Kim, Woo Youn, CHEMISTRY-A EUROPEAN JOURNAL, v.24, no.47, pp.12354 - 12358, 2018-08

6
Label-Free Identification of Lymphocyte Subtypes Using Three-Dimensional Quantitative Phase Imaging and Machine Learning

Yoon, Jonghee; Jo, Youngju; Kim, Young Seo; Yu, Yeongjin; Park, Jiyeon; Lee, Sumin; Park, Wei Sun; et al, JOVE-JOURNAL OF VISUALIZED EXPERIMENTS, v.141, pp.e58305, 2018-11

7
Label-Free Tomographic Imaging of Lipid Droplets in Foam Cells for Machine-Learning-Assisted Therapeutic Evaluation of Targeted Nanodrugs

Park, Sangwoo; Ahn, Jae Won; Jo, YoungJu; Kang, Ha-Young; Kim, Hyun Jung; Cheon, Yeongmi; Kim, Jin Won; et al, ACS NANO, v.14, no.2, pp.1856 - 1865, 2020-02

8
Learning dispatching rules using random forest in flexible job shop scheduling problems

Jun, Sungbum; Lee, Seokcheon; Chun, Hyonho, INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH, v.57, no.10, pp.3290 - 3310, 2019-05

9
Machine learning identification of symmetrized base states of Rydberg atoms

Chong, Daryl Ryan; Kim, Minhyuk; Ahn, Jaewook; Jeong, Heejeong, FRONTIERS OF PHYSICS, v.17, no.1, 2022-02

10
Path Loss Model Based on Machine Learning Using Multi-Dimensional Gaussian Process Regression

Jang, Ki Joung; Park, Sejun; Kim, Junseok; Yoon, Youngkeun; Kim, Chung-Sup; Chong, Young-Jun; Hwang, Ganguk, IEEE ACCESS, v.10, pp.115061 - 115073, 2022

11
Quantitative Phase Imaging and Artificial Intelligence: A Review

Jo, YoungJu; Cho, Hyungjoo; Lee, Sang Yun; Choi, Gunho; Kim, Geon; Min, Hyun-seok; Park, YongKeun, IEEE JOURNAL OF SELECTED TOPICS IN QUANTUM ELECTRONICS, v.25, no.1, pp.6800914, 2019-01

12
Rain Attenuation Prediction Model for Terrestrial Links Using Gaussian Process Regression

Jang, Ki Joung; Yoon, Youngkeun; Kim, Junseok; Kim, Jong Ho; Hwang, Ganguk, IEEE COMMUNICATIONS LETTERS, v.25, no.11, pp.3719 - 3723, 2021-11

13
Reducing Time to Discovery: Materials and Molecular Modeling, Imaging, Informatics, and Integration

Hong, Seungbum; Liow, Chi Hao; Yuk, Jong Min; Byon, Hye Ryung; Yang, Yongsoo; Cho, EunAe; Yeom, Jiwon; et al, ACS NANO, v.15, no.3, pp.3971 - 3995, 2021-02

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