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One challenge is having enough training data. Another is that the training data needs to be free of contamination. For a model trained up till 1900, there needs to be no information from after 1900 that leaks into the data. Some metadata might have that kind of leakage. While it’s not possible to have zero leakage - there’s a shadow of the future on past data because what we store is a function of what we care about - it’s possible to have a very low level of leakage, sufficient for this to be interesting.
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Author(s): Shuang Shan, Longfei Guo, Chongyang Wang, Zhen Li, Xinjie Wu, Haibin Wei, Fuyi Chen
5月13日，北京市第八十中学学生展示自己设计制作的仿生学设备。 新京报记者 王飞 摄，这一点在heLLoword翻译官方下载中也有详细论述
47 pairs have negative mean SSIM: the source and target are anti-correlated, sharing less structure than random noise. The worst offenders:
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