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    <title>PyPI recent updates for paretoflow</title>
    <link>https://pypi.org/project/paretoflow/</link>
    <description>Recent updates to the Python Package Index for paretoflow</description>
    <language>en</language>    <item>
      <title>0.1.5</title>
      <link>https://pypi.org/project/paretoflow/0.1.5/</link>
      <description>Paretoflow is a Python package for offline multi-objective optimization using     Generative Flow Models with Multi Predictors Guidance to approximate the Pareto front.</description>
<author>ye.yuan3@mail.mcgill.ca</author>      <pubDate>Sun, 12 Jan 2025 19:21:57 GMT</pubDate>
    </item>    <item>
      <title>0.1.4</title>
      <link>https://pypi.org/project/paretoflow/0.1.4/</link>
      <description>Paretoflow is a Python package for offline multi-objective optimization using     Generative Flow Models with Multi Predictors Guidance to approximate the Pareto front.</description>
<author>ye.yuan3@mail.mcgill.ca</author>      <pubDate>Sun, 29 Dec 2024 03:34:10 GMT</pubDate>
    </item>    <item>
      <title>0.1.3</title>
      <link>https://pypi.org/project/paretoflow/0.1.3/</link>
      <description>Paretoflow is a Python package for offline multi-objective optimization using     Generative Flow Models with Multi Predictors Guidance to approximate the Pareto front.</description>
<author>ye.yuan3@mail.mcgill.ca</author>      <pubDate>Sun, 29 Dec 2024 03:03:24 GMT</pubDate>
    </item>    <item>
      <title>0.1.2</title>
      <link>https://pypi.org/project/paretoflow/0.1.2/</link>
      <description>Paretoflow is a Python package for offline multi-objective optimization using     Generative Flow Models with Multi Predictors Guidance to approximate the Pareto front.</description>
<author>ye.yuan3@mail.mcgill.ca</author>      <pubDate>Sat, 28 Dec 2024 03:34:25 GMT</pubDate>
    </item>    <item>
      <title>0.1.1</title>
      <link>https://pypi.org/project/paretoflow/0.1.1/</link>
      <description>Paretoflow is a Python package for offline multi-objective optimization using     Generative Flow Models with Multi Predictors Guidance to approximate the Pareto front.</description>
<author>ye.yuan3@mail.mcgill.ca</author>      <pubDate>Sat, 28 Dec 2024 03:29:15 GMT</pubDate>
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