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A Model Falsification Approach to Learning in Non-Stationary Environments for Experimental Design
The application of data driven machine learning and advanced statistical tools to complex physics experiments, such as Magnetic Confinement Nuclear Fusion, can be problematic, due the varying conditions of the systems to be studied. In particular, new experiments have to be planned in unexplored reg...
में बचाया:
| में प्रकाशित: | Sci Rep |
|---|---|
| मुख्य लेखकों: | , , , , |
| स्वरूप: | Artigo |
| भाषा: | Inglês |
| प्रकाशित: |
Nature Publishing Group UK
2019
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| विषय: | |
| ऑनलाइन पहुंच: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6884580/ https://ncbi.nlm.nih.gov/pubmed/31784604 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1038/s41598-019-54145-7 |
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