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| Result Number | Material Type | Add to My Shelf Action | Record Details and Options |
|---|---|---|---|
| 1 |
Material Type: Article
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SHIBR—The Swedish Historical Birth Records: a semi-annotated datasetNeural computing & applications, 2021-11, Vol.33 (22), p.15863-15875 [Peer Reviewed Journal]The Author(s) 2021 ;The Author(s) 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: 0941-0643 ;ISSN: 1433-3058 ;EISSN: 1433-3058 ;DOI: 10.1007/s00521-021-06207-zFull text available |
| 2 |
Material Type: Article
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Learned Causal Method PredictionarXiv.org, 2023-112023. This work is published under http://arxiv.org/licenses/nonexclusive-distrib/1.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;http://arxiv.org/licenses/nonexclusive-distrib/1.0 ;EISSN: 2331-8422 ;DOI: 10.48550/arxiv.2311.03989Full text available |
| 3 |
Material Type: Article
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Towards Causal Foundation Model: on Duality between Causal Inference and AttentionarXiv.org, 2024-052024. This work is published under http://arxiv.org/licenses/nonexclusive-distrib/1.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;http://arxiv.org/licenses/nonexclusive-distrib/1.0 ;EISSN: 2331-8422 ;DOI: 10.48550/arxiv.2310.00809Full text available |
| 4 |
Material Type: Article
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FiP: a Fixed-Point Approach for Causal Generative ModelingarXiv.org, 2024-042024. 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. ;http://creativecommons.org/licenses/by/4.0 ;EISSN: 2331-8422 ;DOI: 10.48550/arxiv.2404.06969Full text available |
| 5 |
Material Type: Article
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Causal Reasoning in the Presence of Latent Confounders via Neural ADMG LearningarXiv.org, 2023-032023. This work is published under http://arxiv.org/licenses/nonexclusive-distrib/1.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;http://arxiv.org/licenses/nonexclusive-distrib/1.0 ;EISSN: 2331-8422 ;DOI: 10.48550/arxiv.2303.12703Full text available |
| 6 |
Material Type: Article
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Perceiving Music Quality with GANsarXiv.org, 2021-042021. This work is published under http://arxiv.org/licenses/nonexclusive-distrib/1.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;http://arxiv.org/licenses/nonexclusive-distrib/1.0 ;EISSN: 2331-8422 ;DOI: 10.48550/arxiv.2006.06287Full text available |
| 7 |
Material Type: Article
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The Essential Role of Causality in Foundation World Models for Embodied AIarXiv.org, 2024-042024. This work is published under http://arxiv.org/licenses/nonexclusive-distrib/1.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;http://arxiv.org/licenses/nonexclusive-distrib/1.0 ;EISSN: 2331-8422 ;DOI: 10.48550/arxiv.2402.06665Full text available |
| 8 |
Material Type: Article
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Understanding Causality with Large Language Models: Feasibility and OpportunitiesarXiv.org, 2023-042023. This work is published under http://arxiv.org/licenses/nonexclusive-distrib/1.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;http://arxiv.org/licenses/nonexclusive-distrib/1.0 ;EISSN: 2331-8422 ;DOI: 10.48550/arxiv.2304.05524Full text available |
| 9 |
Material Type: Article
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Scaling Federated Learning for Fine-tuning of Large Language ModelsarXiv.org, 2021-022021. This work is published under http://arxiv.org/licenses/nonexclusive-distrib/1.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;http://arxiv.org/licenses/nonexclusive-distrib/1.0 ;EISSN: 2331-8422 ;DOI: 10.48550/arxiv.2102.00875Full text available |
| 10 |
Material Type: Article
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Towards Machine Learning on data from Professional CyclistsarXiv.org, 2018-082018. This work is published under http://arxiv.org/licenses/nonexclusive-distrib/1.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;http://arxiv.org/licenses/nonexclusive-distrib/1.0 ;EISSN: 2331-8422 ;DOI: 10.48550/arxiv.1808.00198Full text available |
| 11 |
Material Type: Patent
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MODELLING CAUSATION IN MACHINE LEARNINGDigital Resources/Online E-Resources |
| 12 |
Material Type: Patent
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MODELLING CAUSATION IN MACHINE LEARNINGDigital Resources/Online E-Resources |
| 13 |
Material Type: Patent
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MODELLING CAUSATION IN MACHINE LEARNINGDigital Resources/Online E-Resources |
| 14 |
Material Type: Patent
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MODELLING CAUSATION IN MACHINE LEARNINGDigital Resources/Online E-Resources |
| 15 |
Material Type: Conference Proceeding
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Towards Machine Learning on Data from Professional CyclistsXII World Congress of Performance Analysis of Sport, Opatija, Croatia, 2018, Vol.2018Digital Resources/Online E-Resources |
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