Machine Learning-based Inversion
Machine Learning-Based Inversion is a computational methodology within inverse heat transfer that employs machine learning models to infer unknown thermal properties, boundary conditions, or initial conditions from measured temperature data by learning the underlying mapping between inputs and outputs through data-driven training.
284
Publications
13.5K
Citations
1K
Authors
373
Institutions
Publications per year
2017–2026
218
Parents
284
Deep learning in nano-photonics: inverse design and beyond
Photonics Research · 2021 · 451 citations · Full text
Computing, Computer Science, Physics +13
Xu Chen, Ba Trung Cao, Yong Yuan et al. · Computer Methods in Applied Mechanics and Engineering · 2022 · 225 citations
1–5 of 284
1K
King Abdullah University of Science and Technology, Saudi Arabia
5 publications · 137 citations
5
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5
h-index
4
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4
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4
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1–5 of 1K
373
Tsinghua University
Beijing, China
9 h-index
26 publications
1.3K citations
Massachusetts Institute of Technology
Cambridge, United States
8 h-index
13 publications
2.6K citations

Xi'an Jiaotong University
Xi'an, China
7 h-index
28 publications
968 citations

King Abdullah University of Science and Technology
Jeddah, Saudi Arabia
6 h-index
13 publications
362 citations
University of Michigan
Ann Arbor, United States
6 h-index
13 publications
1.6K citations
Georgia Institute of Technology
Atlanta, United States
5 h-index
20 publications
730 citations

Sun Yat-sen University
Guangzhou, China
5 h-index
18 publications
671 citations
Schlumberger (United States)
Houston, United States
4 h-index
4 publications
211 citations
1–8 of 373
Repository · 15 publications · 496 citations
12
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10 publications · 455 citations
10
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8 publications · 577 citations
8
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6 publications · 229 citations
6
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GRSL · 5 publications · 264 citations
5
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1–5