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CosmoGAN: creating high-fidelity weak lensing convergence maps using Generative Adversarial Networks
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| Published in: | Computational Astrophysics and Cosmology |
|---|---|
| Format: | Online Article RSS Article |
| Published: |
2019
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| Subjects: | |
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| _version_ | 1867301670277349378 |
|---|---|
| collection | WordPress RSS FRELIP Feed Integration |
| container_title | Computational Astrophysics and Cosmology |
| description | |
| discipline_display | Computer Science |
| discipline_facet | Computer Science |
| format | Online Article RSS Article |
| genre | Journal Article |
| id | rss_article:78074 |
| institution | FRELIP |
| journal_source_facet | Computational Astrophysics and Cosmology |
| publishDate | 2019 |
| publishDateSort | 2019 |
| record_format | rss_article |
| spellingShingle | CosmoGAN: creating high-fidelity weak lensing convergence maps using Generative Adversarial Networks Computer Science General Computer Science |
| sub_discipline_display | General |
| sub_discipline_facet | General |
| subject_display | Computer Science General Computer Science Computer Science General Computer Science |
| subject_facet | Computer Science General Computer Science |
| title | CosmoGAN: creating high-fidelity weak lensing convergence maps using Generative Adversarial Networks |
| title_auth | CosmoGAN: creating high-fidelity weak lensing convergence maps using Generative Adversarial Networks |
| title_full | CosmoGAN: creating high-fidelity weak lensing convergence maps using Generative Adversarial Networks |
| title_fullStr | CosmoGAN: creating high-fidelity weak lensing convergence maps using Generative Adversarial Networks |
| title_full_unstemmed | CosmoGAN: creating high-fidelity weak lensing convergence maps using Generative Adversarial Networks |
| title_short | CosmoGAN: creating high-fidelity weak lensing convergence maps using Generative Adversarial Networks |
| title_sort | cosmogan: creating high-fidelity weak lensing convergence maps using generative adversarial networks |
| topic | Computer Science General Computer Science |
| url | https://link.springer.com/article/10.1186/s40668-019-0029-9 |