Time frequency representations and deep convolutional neural networks: a recipe for molecular properties prediction
Time frequency representations and deep convolutional neural networks: a recipe for molecular properties prediction
DOI | Resolve DOI: https://doi.org/10.1109/CCECE53047.2021.9569072 |
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Author | Search for: 1; Search for: 1 |
Affiliation |
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Format | Text, Article |
Conference | 2021 IEEE Canadian Conference on Electrical and Computer Engineering (CCECE), Sept 12-17, 2021, Held Virtually |
Subject | convolutional neural networks; Coulomb matrix; density functional theory; molecular forward design; time-frequency representations |
Abstract | |
Publication date | 2021-10-26 |
Publisher | IEEE |
In | |
Language | English |
Peer reviewed | Yes |
Export citation | Export as RIS |
Report a correction | Report a correction (opens in a new tab) |
Record identifier | 1237329f-fe08-4c94-bca6-65079da70938 |
Record created | 2021-10-28 |
Record modified | 2021-10-29 |
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