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    <title>PyPI recent updates for eqr</title>
    <link>https://pypi.org/project/eqr/</link>
    <description>Recent updates to the Python Package Index for eqr</description>
    <language>en</language>    <item>
      <title>0.1.17</title>
      <link>https://pypi.org/project/eqr/0.1.17/</link>
      <description>A python package to perform quantile regression with more meaningful epistemic uncertainty estimates through training set augmentation using synthetic data. A blend of discriminative and generative models.</description>
<author>sebastiank17@gmail.com</author>      <pubDate>Tue, 26 Nov 2024 08:37:53 GMT</pubDate>
    </item>    <item>
      <title>0.1.16</title>
      <link>https://pypi.org/project/eqr/0.1.16/</link>
      <description>A python package to perform quantile regression with more meaningful epistemic uncertainty estimates through training set augmentation using synthetic data. A blend of discriminative and generative models.</description>
<author>sebastiank17@gmail.com</author>      <pubDate>Mon, 25 Nov 2024 23:02:29 GMT</pubDate>
    </item>    <item>
      <title>0.1.15</title>
      <link>https://pypi.org/project/eqr/0.1.15/</link>
      <description>A python package to perform quantile regression with more meaningful epistemic uncertainty estimates through training set augmentation using synthetic data. A blend of discriminative and generative models.</description>
<author>sebastiank17@gmail.com</author>      <pubDate>Mon, 25 Nov 2024 21:45:54 GMT</pubDate>
    </item>    <item>
      <title>0.1.14</title>
      <link>https://pypi.org/project/eqr/0.1.14/</link>
      <description>A python package to perform quantile regression with more meaningful epistemic uncertainty estimates through training set augmentation using synthetic data. A blend of discriminative and generative models.</description>
<author>sebastiank17@gmail.com</author>      <pubDate>Mon, 25 Nov 2024 19:14:28 GMT</pubDate>
    </item>    <item>
      <title>0.1.13</title>
      <link>https://pypi.org/project/eqr/0.1.13/</link>
      <description>A python package to perform quantile regression with more meaningful epistemic uncertainty estimates through training set augmentation using synthetic data. A blend of discriminative and generative models.</description>
<author>sebastiank17@gmail.com</author>      <pubDate>Mon, 25 Nov 2024 19:07:30 GMT</pubDate>
    </item>    <item>
      <title>0.1.12</title>
      <link>https://pypi.org/project/eqr/0.1.12/</link>
      <description>A python package to perform quantile regression with more meaningful epistemic uncertainty estimates through training set augmentation using synthetic data. A blend of discriminative and generative models.</description>
<author>sebastiank17@gmail.com</author>      <pubDate>Sun, 24 Nov 2024 21:08:21 GMT</pubDate>
    </item>    <item>
      <title>0.1.11</title>
      <link>https://pypi.org/project/eqr/0.1.11/</link>
      <description>A python package to perform quantile regression with more meaningful epistemic uncertainty estimates through training set augmentation using synthetic data. A blend of discriminative and generative models.</description>
<author>sebastiank17@gmail.com</author>      <pubDate>Sat, 23 Nov 2024 08:46:19 GMT</pubDate>
    </item>    <item>
      <title>0.1.10</title>
      <link>https://pypi.org/project/eqr/0.1.10/</link>
      <description>A python package to perform quantile regression with more meaningful epistemic uncertainty estimates through training set augmentation using synthetic data. A blend of discriminative and generative models.</description>
<author>sebastiank17@gmail.com</author>      <pubDate>Sat, 23 Nov 2024 08:26:34 GMT</pubDate>
    </item>    <item>
      <title>0.1.9</title>
      <link>https://pypi.org/project/eqr/0.1.9/</link>
      <description>A python package to perform quantile regression with more meaningful epistemic uncertainty estimates through training set augmentation using synthetic data. A blend of discriminative and generative models.</description>
<author>sebastiank17@gmail.com</author>      <pubDate>Thu, 21 Nov 2024 08:55:55 GMT</pubDate>
    </item>    <item>
      <title>0.1.8</title>
      <link>https://pypi.org/project/eqr/0.1.8/</link>
      <description>A python package to perform quantile regression with more meaningful epistemic uncertainty estimates through training set augmentation using synthetic data. A blend of discriminative and generative models.</description>
<author>sebastiank17@gmail.com</author>      <pubDate>Wed, 20 Nov 2024 23:11:43 GMT</pubDate>
    </item>    <item>
      <title>0.1.7</title>
      <link>https://pypi.org/project/eqr/0.1.7/</link>
      <description>A python package to perform quantile regression with more meaningful epistemic uncertainty estimates through training set augmentation using synthetic data. A blend of discriminative and generative models.</description>
<author>sebastiank17@gmail.com</author>      <pubDate>Wed, 20 Nov 2024 08:43:40 GMT</pubDate>
    </item>    <item>
      <title>0.1.6</title>
      <link>https://pypi.org/project/eqr/0.1.6/</link>
      <description>A python package to perform quantile regression with more meaningful epistemic uncertainty estimates through training set augmentation using synthetic data. A blend of discriminative and generative models.</description>
<author>sebastiank17@gmail.com</author>      <pubDate>Wed, 20 Nov 2024 08:36:55 GMT</pubDate>
    </item>    <item>
      <title>0.1.5</title>
      <link>https://pypi.org/project/eqr/0.1.5/</link>
      <description>A python package to perform quantile regression with more meaningful epistemic uncertainty estimates through training set augmentation using synthetic data. A blend of discriminative and generative models.</description>
<author>sebastiank17@gmail.com</author>      <pubDate>Wed, 20 Nov 2024 08:10:13 GMT</pubDate>
    </item>    <item>
      <title>0.1.4</title>
      <link>https://pypi.org/project/eqr/0.1.4/</link>
      <description>A python package to perform quantile regression with more meaningful epistemic uncertainty estimates through training set augmentation using synthetic data. A blend of discriminative and generative models.</description>
<author>sebastiank17@gmail.com</author>      <pubDate>Wed, 20 Nov 2024 08:00:20 GMT</pubDate>
    </item>    <item>
      <title>0.1.3</title>
      <link>https://pypi.org/project/eqr/0.1.3/</link>
      <description>A python package to perform quantile regression with more meaningful epistemic uncertainty estimates through training set augmentation using synthetic data. A blend of discriminative and generative models.</description>
<author>sebastiank17@gmail.com</author>      <pubDate>Tue, 19 Nov 2024 19:43:34 GMT</pubDate>
    </item>    <item>
      <title>0.1.2</title>
      <link>https://pypi.org/project/eqr/0.1.2/</link>
      <description>A python package to perform quantile regression with more meaningful epistemic uncertainty estimates through training set augmentation using synthetic data. A blend of discriminative and generative models.</description>
<author>sebastiank17@gmail.com</author>      <pubDate>Tue, 19 Nov 2024 19:38:38 GMT</pubDate>
    </item>    <item>
      <title>0.1.1</title>
      <link>https://pypi.org/project/eqr/0.1.1/</link>
      <description>A python package to perform quantile regression with more meaningful epistemic uncertainty estimates through training set augmentation using synthetic data. A blend of discriminative and generative models.</description>
<author>sebastiank17@gmail.com</author>      <pubDate>Mon, 18 Nov 2024 22:28:15 GMT</pubDate>
    </item>    <item>
      <title>0.1.0</title>
      <link>https://pypi.org/project/eqr/0.1.0/</link>
      <description>A python package to perform quantile regression with more meaningful epistemic uncertainty estimates through training set augmentation using synthetic data. A blend of discriminative and generative models.</description>
<author>sebastiank17@gmail.com</author>      <pubDate>Mon, 18 Nov 2024 16:35:51 GMT</pubDate>
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