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    <title>PyPI recent updates for maxentsolver</title>
    <link>https://pypi.org/project/maxentsolver/</link>
    <description>Recent updates to the Python Package Index for maxentsolver</description>
    <language>en</language>    <item>
      <title>0.2.5</title>
      <link>https://pypi.org/project/maxentsolver/0.2.5/</link>
      <description>A Python package for fitting maximum entropy models to BOLD time-series data. The toolkit automatically binarizes fMRI/BOLD signals, constructs pairwise maximum entropy (MaxEnt) models, and provides utilities to analyze the inferred interaction network. Most functionality is not implemented yet.</description>
      <pubDate>Tue, 09 Dec 2025 10:27:42 GMT</pubDate>
    </item>    <item>
      <title>0.2.4</title>
      <link>https://pypi.org/project/maxentsolver/0.2.4/</link>
      <description>A Python package for fitting maximum entropy models to BOLD time-series data. The toolkit automatically binarizes fMRI/BOLD signals, constructs pairwise maximum entropy (MaxEnt) models, and provides utilities to analyze the inferred interaction network. Most functionality is not implemented yet.</description>
      <pubDate>Tue, 09 Dec 2025 10:19:31 GMT</pubDate>
    </item>    <item>
      <title>0.2.3</title>
      <link>https://pypi.org/project/maxentsolver/0.2.3/</link>
      <description>A Python package for fitting maximum entropy models to BOLD time-series data. The toolkit automatically binarizes fMRI/BOLD signals, constructs pairwise maximum entropy (MaxEnt) models, and provides utilities to analyze the inferred interaction network. Most functionality is not implemented yet.</description>
      <pubDate>Mon, 08 Dec 2025 20:43:02 GMT</pubDate>
    </item>    <item>
      <title>0.2.2</title>
      <link>https://pypi.org/project/maxentsolver/0.2.2/</link>
      <description>A Python package for fitting maximum entropy models to BOLD time-series data. The toolkit automatically binarizes fMRI/BOLD signals, constructs pairwise maximum entropy (MaxEnt) models, and provides utilities to analyze the inferred interaction network. Most functionality is not implemented yet.</description>
      <pubDate>Wed, 26 Nov 2025 12:09:31 GMT</pubDate>
    </item>    <item>
      <title>0.2.1</title>
      <link>https://pypi.org/project/maxentsolver/0.2.1/</link>
      <description>A Python package for fitting maximum entropy models to BOLD time-series data. The toolkit automatically binarizes fMRI/BOLD signals, constructs pairwise maximum entropy (MaxEnt) models, and provides utilities to analyze the inferred interaction network. Most functionality is not implemented yet.</description>
      <pubDate>Wed, 26 Nov 2025 11:59:23 GMT</pubDate>
    </item>    <item>
      <title>0.2.0</title>
      <link>https://pypi.org/project/maxentsolver/0.2.0/</link>
      <description>A Python package for fitting maximum entropy models to BOLD time-series data. The toolkit automatically binarizes fMRI/BOLD signals, constructs pairwise maximum entropy (MaxEnt) models, and provides utilities to analyze the inferred interaction network. Most functionality is not implemented yet.</description>
      <pubDate>Tue, 25 Nov 2025 03:11:00 GMT</pubDate>
    </item>    <item>
      <title>0.1.2</title>
      <link>https://pypi.org/project/maxentsolver/0.1.2/</link>
      <description>A Python package for fitting maximum entropy models to BOLD time-series data. The toolkit automatically binarizes fMRI/BOLD signals, constructs pairwise maximum entropy (MaxEnt) models, and provides utilities to analyze the inferred interaction network. Most functionality is not implemented yet.</description>
      <pubDate>Mon, 24 Nov 2025 17:02:07 GMT</pubDate>
    </item>    <item>
      <title>0.1.1</title>
      <link>https://pypi.org/project/maxentsolver/0.1.1/</link>
      <description>A Python package for fitting maximum entropy models to BOLD time-series data. The toolkit automatically binarizes fMRI/BOLD signals, constructs pairwise maximum entropy (MaxEnt) models, and provides utilities to analyze the inferred interaction network. Most functionality is not implemented yet.</description>
      <pubDate>Mon, 24 Nov 2025 09:57:21 GMT</pubDate>
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