<?xml version="1.0" encoding="UTF-8"?>
<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:dc="http://purl.org/dc/elements/1.1/">
  <channel>
    <title>DEV Community: Paperium</title>
    <description>The latest articles on DEV Community by Paperium (@paperium).</description>
    <link>https://dev.to/paperium</link>
    <image>
      <url>https://media2.dev.to/dynamic/image/width=90,height=90,fit=cover,gravity=auto,format=auto/https:%2F%2Fdev-to-uploads.s3.amazonaws.com%2Fuploads%2Fuser%2Fprofile_image%2F3573644%2F68c92d3d-c837-4124-a237-e49ffe38ea6e.png</url>
      <title>DEV Community: Paperium</title>
      <link>https://dev.to/paperium</link>
    </image>
    <atom:link rel="self" type="application/rss+xml" href="https://dev.to/feed/paperium"/>
    <language>en</language>
    <item>
      <title>Clova Baseline System for the VoxCeleb Speaker Recognition Challenge 2020</title>
      <dc:creator>Paperium</dc:creator>
      <pubDate>Tue, 12 May 2026 02:40:27 +0000</pubDate>
      <link>https://dev.to/paperium/clova-baseline-system-for-the-voxceleb-speaker-recognition-challenge-2020-2igf</link>
      <guid>https://dev.to/paperium/clova-baseline-system-for-the-voxceleb-speaker-recognition-challenge-2020-2igf</guid>
      <description>&lt;p&gt;{{ $json.postContent }}&lt;/p&gt;

</description>
      <category>ai</category>
      <category>deeplearning</category>
      <category>computerscience</category>
      <category>machinelearning</category>
    </item>
    <item>
      <title>Scale-Invariant Convolutional Neural Networks</title>
      <dc:creator>Paperium</dc:creator>
      <pubDate>Tue, 12 May 2026 01:30:28 +0000</pubDate>
      <link>https://dev.to/paperium/scale-invariant-convolutional-neural-networks-10mh</link>
      <guid>https://dev.to/paperium/scale-invariant-convolutional-neural-networks-10mh</guid>
      <description>&lt;p&gt;{{ $json.postContent }}&lt;/p&gt;

</description>
      <category>ai</category>
      <category>deeplearning</category>
      <category>computerscience</category>
      <category>machinelearning</category>
    </item>
    <item>
      <title>A PAC-Bayesian Tutorial with A Dropout Bound</title>
      <dc:creator>Paperium</dc:creator>
      <pubDate>Tue, 12 May 2026 00:20:27 +0000</pubDate>
      <link>https://dev.to/paperium/a-pac-bayesian-tutorial-with-a-dropout-bound-2jep</link>
      <guid>https://dev.to/paperium/a-pac-bayesian-tutorial-with-a-dropout-bound-2jep</guid>
      <description>&lt;p&gt;{{ $json.postContent }}&lt;/p&gt;

</description>
      <category>ai</category>
      <category>deeplearning</category>
      <category>computerscience</category>
      <category>machinelearning</category>
    </item>
    <item>
      <title>NeuralPower: Predict and Deploy Energy-Efficient Convolutional Neural Networks</title>
      <dc:creator>Paperium</dc:creator>
      <pubDate>Mon, 11 May 2026 23:10:27 +0000</pubDate>
      <link>https://dev.to/paperium/neuralpower-predict-and-deploy-energy-efficient-convolutional-neural-networks-3hl0</link>
      <guid>https://dev.to/paperium/neuralpower-predict-and-deploy-energy-efficient-convolutional-neural-networks-3hl0</guid>
      <description>&lt;p&gt;{{ $json.postContent }}&lt;/p&gt;

</description>
      <category>ai</category>
      <category>deeplearning</category>
      <category>computerscience</category>
      <category>machinelearning</category>
    </item>
    <item>
      <title>AdaBatch: Adaptive Batch Sizes for Training Deep Neural Networks</title>
      <dc:creator>Paperium</dc:creator>
      <pubDate>Mon, 11 May 2026 22:00:27 +0000</pubDate>
      <link>https://dev.to/paperium/adabatch-adaptive-batch-sizes-for-training-deep-neural-networks-6dh</link>
      <guid>https://dev.to/paperium/adabatch-adaptive-batch-sizes-for-training-deep-neural-networks-6dh</guid>
      <description>&lt;p&gt;{{ $json.postContent }}&lt;/p&gt;

</description>
      <category>ai</category>
      <category>deeplearning</category>
      <category>computerscience</category>
      <category>machinelearning</category>
    </item>
    <item>
      <title>Dissecting the Graphcore IPU Architecture via Microbenchmarking</title>
      <dc:creator>Paperium</dc:creator>
      <pubDate>Mon, 11 May 2026 20:50:28 +0000</pubDate>
      <link>https://dev.to/paperium/dissecting-the-graphcore-ipu-architecture-via-microbenchmarking-4pce</link>
      <guid>https://dev.to/paperium/dissecting-the-graphcore-ipu-architecture-via-microbenchmarking-4pce</guid>
      <description>&lt;p&gt;{{ $json.postContent }}&lt;/p&gt;

</description>
      <category>ai</category>
      <category>deeplearning</category>
      <category>computerscience</category>
      <category>machinelearning</category>
    </item>
    <item>
      <title>AlphaEvolve: A coding agent for scientific and algorithmic discovery</title>
      <dc:creator>Paperium</dc:creator>
      <pubDate>Mon, 11 May 2026 19:40:28 +0000</pubDate>
      <link>https://dev.to/paperium/alphaevolve-a-coding-agent-for-scientific-and-algorithmic-discovery-3e79</link>
      <guid>https://dev.to/paperium/alphaevolve-a-coding-agent-for-scientific-and-algorithmic-discovery-3e79</guid>
      <description>&lt;p&gt;{{ $json.postContent }}&lt;/p&gt;

</description>
      <category>ai</category>
      <category>deeplearning</category>
      <category>computerscience</category>
      <category>machinelearning</category>
    </item>
    <item>
      <title>A Comparative Study of Adaptive Crossover Operators for Genetic Algorithms toResolve the Traveling Salesman Problem</title>
      <dc:creator>Paperium</dc:creator>
      <pubDate>Mon, 11 May 2026 18:30:32 +0000</pubDate>
      <link>https://dev.to/paperium/a-comparative-study-of-adaptive-crossover-operators-for-genetic-algorithms-toresolve-the-traveling-4c65</link>
      <guid>https://dev.to/paperium/a-comparative-study-of-adaptive-crossover-operators-for-genetic-algorithms-toresolve-the-traveling-4c65</guid>
      <description>&lt;p&gt;{{ $json.postContent }}&lt;/p&gt;

</description>
      <category>ai</category>
      <category>deeplearning</category>
      <category>computerscience</category>
      <category>machinelearning</category>
    </item>
    <item>
      <title>Self-Organized Stigmergic Document Maps: Environment as a Mechanism for ContextLearning</title>
      <dc:creator>Paperium</dc:creator>
      <pubDate>Mon, 11 May 2026 17:30:28 +0000</pubDate>
      <link>https://dev.to/paperium/self-organized-stigmergic-document-maps-environment-as-a-mechanism-for-contextlearning-dfj</link>
      <guid>https://dev.to/paperium/self-organized-stigmergic-document-maps-environment-as-a-mechanism-for-contextlearning-dfj</guid>
      <description>&lt;p&gt;{{ $json.postContent }}&lt;/p&gt;

</description>
      <category>ai</category>
      <category>deeplearning</category>
      <category>computerscience</category>
      <category>machinelearning</category>
    </item>
    <item>
      <title>Horizon: Facebook's Open Source Applied Reinforcement Learning Platform</title>
      <dc:creator>Paperium</dc:creator>
      <pubDate>Mon, 11 May 2026 16:20:28 +0000</pubDate>
      <link>https://dev.to/paperium/horizon-facebooks-open-source-applied-reinforcement-learning-platform-2bn0</link>
      <guid>https://dev.to/paperium/horizon-facebooks-open-source-applied-reinforcement-learning-platform-2bn0</guid>
      <description>&lt;p&gt;{{ $json.postContent }}&lt;/p&gt;

</description>
      <category>ai</category>
      <category>deeplearning</category>
      <category>computerscience</category>
      <category>machinelearning</category>
    </item>
    <item>
      <title>Traffic Accident Analysis Using Decision Trees and Neural Networks</title>
      <dc:creator>Paperium</dc:creator>
      <pubDate>Mon, 11 May 2026 15:10:28 +0000</pubDate>
      <link>https://dev.to/paperium/traffic-accident-analysis-using-decision-trees-and-neural-networks-3o05</link>
      <guid>https://dev.to/paperium/traffic-accident-analysis-using-decision-trees-and-neural-networks-3o05</guid>
      <description>&lt;p&gt;{{ $json.postContent }}&lt;/p&gt;

</description>
      <category>ai</category>
      <category>deeplearning</category>
      <category>computerscience</category>
      <category>machinelearning</category>
    </item>
    <item>
      <title>A Survey on Deep Learning-based Non-Invasive Brain Signals:Recent Advances andNew Frontiers</title>
      <dc:creator>Paperium</dc:creator>
      <pubDate>Mon, 11 May 2026 14:00:29 +0000</pubDate>
      <link>https://dev.to/paperium/a-survey-on-deep-learning-based-non-invasive-brain-signalsrecent-advances-andnew-frontiers-36fh</link>
      <guid>https://dev.to/paperium/a-survey-on-deep-learning-based-non-invasive-brain-signalsrecent-advances-andnew-frontiers-36fh</guid>
      <description>&lt;p&gt;{{ $json.postContent }}&lt;/p&gt;

</description>
      <category>ai</category>
      <category>deeplearning</category>
      <category>computerscience</category>
      <category>machinelearning</category>
    </item>
  </channel>
</rss>
