<?xml version="1.0" encoding="UTF-8"?>
<rss version="2.0">
  <channel>
    <title>PyPI recent updates for ibnr</title>
    <link>https://pypi.org/project/ibnr/</link>
    <description>Recent updates to the Python Package Index for ibnr</description>
    <language>en</language>    <item>
      <title>0.5.9</title>
      <link>https://pypi.org/project/ibnr/0.5.9/</link>
      <description>Gallery-centric probabilistic loss reserving: Bayesian MCMC and neural network methods with mandatory evaluation, over a long-format triangle data layer.</description>
<author>ethan.yskang@gmail.com</author>      <pubDate>Mon, 07 Sep 2026 05:23:42 GMT</pubDate>
    </item>    <item>
      <title>0.5.8</title>
      <link>https://pypi.org/project/ibnr/0.5.8/</link>
      <description>Gallery-centric probabilistic loss reserving: Bayesian MCMC and neural network methods with mandatory evaluation, over a long-format triangle data layer.</description>
<author>ethan.yskang@gmail.com</author>      <pubDate>Tue, 25 Aug 2026 05:20:32 GMT</pubDate>
    </item>    <item>
      <title>0.5.7</title>
      <link>https://pypi.org/project/ibnr/0.5.7/</link>
      <description>Gallery-centric probabilistic loss reserving: Bayesian MCMC and neural network methods with mandatory evaluation, over a long-format triangle data layer.</description>
<author>ethan.yskang@gmail.com</author>      <pubDate>Tue, 25 Aug 2026 03:51:25 GMT</pubDate>
    </item>    <item>
      <title>0.5.6</title>
      <link>https://pypi.org/project/ibnr/0.5.6/</link>
      <description>Gallery-centric probabilistic loss reserving: Bayesian MCMC and neural network methods with mandatory evaluation, over a long-format triangle data layer.</description>
<author>ethan.yskang@gmail.com</author>      <pubDate>Wed, 12 Aug 2026 07:24:01 GMT</pubDate>
    </item>    <item>
      <title>0.5.5</title>
      <link>https://pypi.org/project/ibnr/0.5.5/</link>
      <description>Gallery-centric probabilistic loss reserving: Bayesian MCMC and neural network methods with mandatory evaluation, over a long-format triangle data layer.</description>
<author>ethan.yskang@gmail.com</author>      <pubDate>Thu, 06 Aug 2026 08:25:56 GMT</pubDate>
    </item>    <item>
      <title>0.5.4</title>
      <link>https://pypi.org/project/ibnr/0.5.4/</link>
      <description>Gallery-centric probabilistic loss reserving: Bayesian MCMC and neural network methods with mandatory evaluation, over a long-format triangle data layer.</description>
<author>ethan.yskang@gmail.com</author>      <pubDate>Wed, 05 Aug 2026 09:21:59 GMT</pubDate>
    </item>    <item>
      <title>0.5.3</title>
      <link>https://pypi.org/project/ibnr/0.5.3/</link>
      <description>Gallery-centric probabilistic loss reserving: Bayesian MCMC and neural network methods with mandatory evaluation, over a long-format triangle data layer.</description>
<author>ethan.yskang@gmail.com</author>      <pubDate>Wed, 05 Aug 2026 02:42:10 GMT</pubDate>
    </item>    <item>
      <title>0.5.2</title>
      <link>https://pypi.org/project/ibnr/0.5.2/</link>
      <description>Gallery-centric probabilistic loss reserving: Bayesian MCMC and neural network methods with mandatory evaluation, over a long-format triangle data layer.</description>
<author>ethan.yskang@gmail.com</author>      <pubDate>Thu, 30 Jul 2026 05:08:34 GMT</pubDate>
    </item>    <item>
      <title>0.5.1</title>
      <link>https://pypi.org/project/ibnr/0.5.1/</link>
      <description>Gallery-centric probabilistic loss reserving: Bayesian MCMC and neural network methods with mandatory evaluation, over a long-format triangle data layer.</description>
<author>ethan.yskang@gmail.com</author>      <pubDate>Thu, 30 Jul 2026 04:48:53 GMT</pubDate>
    </item>    <item>
      <title>0.5.0</title>
      <link>https://pypi.org/project/ibnr/0.5.0/</link>
      <description>Gallery-centric probabilistic loss reserving: Bayesian MCMC and neural network methods with mandatory evaluation, over a long-format triangle data layer.</description>
<author>ethan.yskang@gmail.com</author>      <pubDate>Wed, 29 Jul 2026 00:10:07 GMT</pubDate>
    </item>    <item>
      <title>0.4.0</title>
      <link>https://pypi.org/project/ibnr/0.4.0/</link>
      <description>Gallery-centric probabilistic loss reserving: Bayesian MCMC and neural network methods with mandatory evaluation, over a long-format triangle data layer.</description>
<author>ethan.yskang@gmail.com</author>      <pubDate>Fri, 24 Jul 2026 06:26:39 GMT</pubDate>
    </item>    <item>
      <title>0.3.0</title>
      <link>https://pypi.org/project/ibnr/0.3.0/</link>
      <description>Gallery-centric probabilistic loss reserving: Bayesian MCMC and neural network methods with mandatory evaluation, over a long-format triangle data layer.</description>
<author>ethan.yskang@gmail.com</author>      <pubDate>Fri, 24 Jul 2026 02:36:26 GMT</pubDate>
    </item>    <item>
      <title>0.2.0</title>
      <link>https://pypi.org/project/ibnr/0.2.0/</link>
      <description>Gallery-centric probabilistic loss reserving: Bayesian MCMC and neural network methods with mandatory evaluation, over a long-format triangle data layer.</description>
<author>ethan.yskang@gmail.com</author>      <pubDate>Thu, 23 Jul 2026 23:48:29 GMT</pubDate>
    </item>  </channel>
</rss>