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    <title>PyPI recent updates for deepx-pack</title>
    <link>https://pypi.org/project/deepx-pack/</link>
    <description>Recent updates to the Python Package Index for deepx-pack</description>
    <language>en</language>    <item>
      <title>1.0.6.post3</title>
      <link>https://pypi.org/project/deepx-pack/1.0.6.post3/</link>
      <description>DeepH-pack is a general-purpose neural network package for deep-learning electronic structure calculations. As the latest evolution of the DeepH framework, it integrates all prior methodologies into a unified, cohesive toolkit. This enhanced version has been fully rebuilt using JAX, delivering greater computational efficiency and expanded functionality.</description>
<author>deeph-pack@outlook.com</author>      <pubDate>Mon, 19 Jan 2026 06:07:06 GMT</pubDate>
    </item>    <item>
      <title>1.0.6.post2</title>
      <link>https://pypi.org/project/deepx-pack/1.0.6.post2/</link>
      <description>DeepH-pack, the latest iteration of DeepH, unites all the preceding DeepH methodologies into a cohesive package. This advanced version has been meticulously rewritten with JAX, enhancing its efficiency and capabilities.</description>
<author>deeph-pack@outlook.com</author>      <pubDate>Fri, 16 Jan 2026 10:03:52 GMT</pubDate>
    </item>    <item>
      <title>1.0.6.post1</title>
      <link>https://pypi.org/project/deepx-pack/1.0.6.post1/</link>
      <description>DeepH-pack, the latest iteration of DeepH, unites all the preceding DeepH methodologies into a cohesive package. This advanced version has been meticulously rewritten with JAX, enhancing its efficiency and capabilities.</description>
<author>duanw@tsinghua.com, yongxu@tsinghua.com, deeph-pack@outlook.com</author>      <pubDate>Fri, 16 Jan 2026 09:50:29 GMT</pubDate>
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