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| Result Number | Material Type | Add to My Shelf Action | Record Details and Options |
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| 1 |
Material Type: Article
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Prediction of chemical reaction yields using deep learningMachine learning: science and technology, 2021-03, Vol.2 (1), p.15016 [Peer Reviewed Journal]2021. This work is published under http://creativecommons.org/licenses/by/4.0 (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 2632-2153 ;EISSN: 2632-2153 ;DOI: 10.1088/2632-2153/abc81dFull text available |
| 2 |
Material Type: Article
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Novel heuristic-based hybrid ResNeXt with recurrent neural network to handle multi class classification of sentiment analysisMachine learning: science and technology, 2023-03, Vol.4 (1), p.15033 [Peer Reviewed Journal]2023 The Author(s). Published by IOP Publishing Ltd ;2023 The Author(s). Published by IOP Publishing Ltd. This work is published under http://creativecommons.org/licenses/by/4.0 (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 2632-2153 ;EISSN: 2632-2153 ;DOI: 10.1088/2632-2153/acc0d5 ;CODEN: MLSTCKFull text available |
| 3 |
Material Type: Article
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Standardizing chemical compounds with language modelsMachine learning: science and technology, 2023-09, Vol.4 (3), p.35014 [Peer Reviewed Journal]2023 The Author(s). Published by IOP Publishing Ltd ;2023 The Author(s). Published by IOP Publishing Ltd. This work is published under http://creativecommons.org/licenses/by/4.0 (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 2632-2153 ;EISSN: 2632-2153 ;DOI: 10.1088/2632-2153/ace878 ;CODEN: MLSTCKFull text available |
| 4 |
Material Type: Article
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SMILES-X: autonomous molecular compounds characterization for small datasets without descriptorsMachine learning: science and technology, 2020-06, Vol.1 (2), p.25004 [Peer Reviewed Journal]2020 The Author(s). Published by IOP Publishing Ltd ;2020. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 2632-2153 ;EISSN: 2632-2153 ;DOI: 10.1088/2632-2153/ab57f3 ;CODEN: MLSTCKFull text available |
| 5 |
Material Type: Article
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Categorical representation learning: morphism is all you needMachine learning: science and technology, 2022-03, Vol.3 (1), p.15016 [Peer Reviewed Journal]2021 The Author(s). Published by IOP Publishing Ltd ;2022. This work is published under http://creativecommons.org/licenses/by/4.0 (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 2632-2153 ;EISSN: 2632-2153 ;DOI: 10.1088/2632-2153/ac2c5d ;CODEN: MLSTCKFull text available |
| 6 |
Material Type: Article
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Chemformer: a pre-trained transformer for computational chemistryMachine learning: science and technology, 2022-03, Vol.3 (1), p.15022 [Peer Reviewed Journal]2022 The Author(s). Published by IOP Publishing Ltd ;2022 The Author(s). Published by IOP Publishing Ltd. This work is published under http://creativecommons.org/licenses/by/4.0 (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 2632-2153 ;EISSN: 2632-2153 ;DOI: 10.1088/2632-2153/ac3ffb ;CODEN: MLSTCKFull text available |
| 7 |
Material Type: Article
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ATSFCNN: A Novel Attention-based Triple-Stream Fused CNN Model for Hyperspectral Image ClassificationMachine learning: science and technology, 2024-03, Vol.5 (1), p.015024 [Peer Reviewed Journal]2024 The Author(s). Published by IOP Publishing Ltd. This work is published under http://creativecommons.org/licenses/by/4.0 (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 2632-2153 ;EISSN: 2632-2153 ;DOI: 10.1088/2632-2153/ad1d05Full text available |
| 8 |
Material Type: Article
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Deblending Galaxies with Generative Adversarial NetworksThe Astrophysical journal, 2022-12, Vol.941 (2), p.141 [Peer Reviewed Journal]2022. The Author(s). Published by the American Astronomical Society. ;2022. The Author(s). Published by the American Astronomical Society. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 0004-637X ;EISSN: 1538-4357 ;DOI: 10.3847/1538-4357/aca1b8Full text available |
| 9 |
Material Type: Article
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Improving Astronomical Time-series Classification via Data Augmentation with Generative Adversarial NetworksThe Astrophysical journal, 2022-08, Vol.935 (1), p.23 [Peer Reviewed Journal]2022. The Author(s). Published by the American Astronomical Society. ;2022. The Author(s). Published by the American Astronomical Society. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 0004-637X ;EISSN: 1538-4357 ;DOI: 10.3847/1538-4357/ac6f5aFull text available |
| 10 |
Material Type: Article
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Synthetic pre-training for neural-network interatomic potentialsMachine learning: science and technology, 2024-03, Vol.5 (1), p.15003 [Peer Reviewed Journal]2024 The Author(s). Published by IOP Publishing Ltd. This work is published under http://creativecommons.org/licenses/by/4.0 (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 2632-2153 ;EISSN: 2632-2153 ;DOI: 10.1088/2632-2153/ad1626Full text available |
| 11 |
Material Type: Article
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Exploiting data diversity in multi-domain federated learningMachine learning: science and technology, 2024-06, Vol.5 (2), p.025041 [Peer Reviewed Journal]2024 The Author(s). Published by IOP Publishing Ltd. This work is published under http://creativecommons.org/licenses/by/4.0 (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;EISSN: 2632-2153 ;DOI: 10.1088/2632-2153/ad4768Full text available |
| 12 |
Material Type: Article
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Improving materials property predictions for graph neural networks with minimal feature engineeringMachine learning: science and technology, 2023-09, Vol.4 (3), p.35030 [Peer Reviewed Journal]2023 The Author(s). Published by IOP Publishing Ltd. This work is published under http://creativecommons.org/licenses/by/4.0 (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 2632-2153 ;EISSN: 2632-2153 ;DOI: 10.1088/2632-2153/acefabFull text available |
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