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One of the most promising applications of machine learning in computational physics is the accelerated solution of partial differential equations (PDEs). The main goal of a machine learning-based partial differential equation solver is to produce solutions that are accurate enough faster than standard numerical methods to serve as a baseline comparison. Hana mua mākou i kahi loiloi systemtic o ka mina Keyke Kūlana e waiho ai i nā kūlike likeʻole. ʻO nā pepa āpau e hōʻike ana i ka hoʻohanaʻana o ML e hoʻoponopono i nā hoʻohālikelike likeʻole a me ka hoʻopiʻiʻana ma luna o nā helu helu maʻamau. Second, we found evidence of widespread reporting bias, particularly in outcome reporting and publication bias. Hoʻomaʻamaʻa mākou i ka noiʻiʻana o ka mīkini hana me ka hoʻoponoponoʻana i nā hoʻohālikelike likeʻole: hiki i nāʻikepili i hiki ke alakaʻi i lalo o nā hopena maikaʻiʻole. Ma ka'āpana nui,ʻikeʻia kēia mau pilikia e like me nā mea e like me nā mea i hala i hala We call for bottom-up cultural change to minimize biased reporting and top-down structural reform to reduce perverse incentives to do so.
ʻO ka papa inoa o nā mea kākau a me nāʻatikala i hanaʻia e ka loiloi'ōnaehana, a me ka heluʻana o kēlā me kēiaʻatikala ma ka https:
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Post Times: Sep-29-2024