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pro vyhledávání: '"Boscoe, Bernie"'
We present a dataset built for machine learning applications consisting of galaxy photometry, images, spectroscopic redshifts, and structural properties. This dataset comprises 286,401 galaxy images and photometry from the Hyper-Suprime-Cam Survey PD
Externí odkaz:
http://arxiv.org/abs/2410.00271
Generative models producing images have enormous potential to advance discoveries across scientific fields and require metrics capable of quantifying the high dimensional output. We propose that astrophysics data, such as galaxy images, can test gene
Externí odkaz:
http://arxiv.org/abs/2407.07229
We present results exploring the role that probabilistic deep learning models can play in cosmology from large-scale astronomical surveys through photometric redshift (photo-z) estimation. Photo-z uncertainty estimates are critical for the science go
Externí odkaz:
http://arxiv.org/abs/2306.13179
In this work, we identify elements of effective machine learning datasets in astronomy and present suggestions for their design and creation. Machine learning has become an increasingly important tool for analyzing and understanding the large-scale f
Externí odkaz:
http://arxiv.org/abs/2211.14401
We present results exploring the role that probabilistic deep learning models can play in cosmology from large scale astronomical surveys through estimating the distances to galaxies (redshifts) from photometry. Due to the massive scale of data comin
Externí odkaz:
http://arxiv.org/abs/2202.07121
Akademický článek
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Akademický článek
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Autor:
Boscoe, Bernie
A poster presented at the SIAM CSE21 conference, minisymposterium PP7: Software Productivity and Sustainability for CSE.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2bf17439e5290486a883969d1f507846
Autor:
Boscoe, Bernie
Poster for SIAM 2021 workshop on sustainability and maintenance in software for scientific research
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::922092436c1dca4f62040c73ed330e2a