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    <title>Chaos Computer Club - realraum (high quality mp4)</title>
    <link>https://media.ccc.de/c/realraum</link>
    <description> This feed contains all events from realraum as mp4</description>
    <copyright>see video outro</copyright>
    <lastBuildDate>Thu, 12 Feb 2026 22:20:54 -0000</lastBuildDate>
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      <title>Chaos Computer Club - realraum (high quality mp4)</title>
      <link>https://media.ccc.de/c/realraum</link>
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      <title>Variational Autoencorders: the cognitive scientist&#39;s favorite deep learning tool (realraum)</title>
      <link>https://media.ccc.de/v/realraum-variational-autoencorders-the-cognitive-scientist-s-favorite-deep-learning-tool</link>
      <description>Variational Autoencoders (VAEs) were first introduced as early concept learners in the vision domain. Since then, they have become a staple tool in generative modeling, representation learning, and unsupervised learning more broadly. Their use as analogues of human cognition is one of the first steps towards the understanding of more complex cognitive models leading up to models of human brain function and behavior. As part of a series of talks on cognitive science and deep learning at the realraum in Graz, this presentation will focus on the role of VAEs in cognitive science research.

Topics:
 - Supervised vs. unsupervised learning
 - Deep Learning basics: classifiers and backpropagation
 - Autoencoders: architecture, training, embedding, and generative modeling
 - Variational Autoencoders: statistical latent space, and the reparametrization trick
 - Training VAEs: loss functions, optimization, and the KL divergence
 - Concept learning: VAEs in cognitive science

https://creativecommons.org/licenses/by-sa/4.0/
about this event: https://cfp.realraum.at/realraum-october/talk/LHH3M9/
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      <enclosure url="https://cdn.media.ccc.de/contributors/realraum/h264-hd/realraum-1-eng-Variational_Autoencorders_the_cognitive_scientists_favorite_deep_learning_tool_hd.mp4"
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      <pubDate>Fri, 24 Oct 2025 19:00:00 +0200</pubDate>
      <guid isPermaLink="true">https://cdn.media.ccc.de/contributors/realraum/h264-hd/realraum-1-eng-Variational_Autoencorders_the_cognitive_scientists_favorite_deep_learning_tool_hd.mp4?1761419467</guid>
      <dc:identifier>2b135a57-c750-5084-9d3b-28391b586e87</dc:identifier>
      <dc:date>2025-10-24T19:00:00+02:00</dc:date>
      <itunes:author>Xiutik</itunes:author>
      <itunes:explicit>No</itunes:explicit>
      <itunes:keywords>1, 2025, realraum, LoTHR, LoTHR, realraum-eng, realraum, r3, r3talks, graz, Day 1</itunes:keywords>
      <itunes:summary>Variational Autoencoders (VAEs) were first introduced as early concept learners in the vision domain. Since then, they have become a staple tool in generative modeling, representation learning, and unsupervised learning more broadly. Their use as analogues of human cognition is one of the first steps towards the understanding of more complex cognitive models leading up to models of human brain function and behavior. As part of a series of talks on cognitive science and deep learning at the realraum in Graz, this presentation will focus on the role of VAEs in cognitive science research.

Topics:
 - Supervised vs. unsupervised learning
 - Deep Learning basics: classifiers and backpropagation
 - Autoencoders: architecture, training, embedding, and generative modeling
 - Variational Autoencoders: statistical latent space, and the reparametrization trick
 - Training VAEs: loss functions, optimization, and the KL divergence
 - Concept learning: VAEs in cognitive science

https://creativecommons.org/licenses/by-sa/4.0/
about this event: https://cfp.realraum.at/realraum-october/talk/LHH3M9/
</itunes:summary>
      <itunes:duration>00:41:56</itunes:duration>
      <itunes:image href="https://static.media.ccc.de/media/contributors/realraum/1-2b135a57-c750-5084-9d3b-28391b586e87.jpg"/>
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      <title>Kalman Filter und Sensor Fusion (realraum)</title>
      <link>https://media.ccc.de/v/realraum-56371-kalman-filter-und-sensor</link>
      <description>Ein kurzer Vortrag, der die Vor- und Nachteile einzelner Sensoren aufzeigt, was die Entwicklung der Sensor Fusion motivierte. Es wird ein Überblick geschaffen, wie man vom einfachen Complementary Filter zum Kalman Filter kommt und wie man diesen adaptiert um nichtlineare Zustände zu berechnen. Diese Erweiterung ist als Extended Kalman Filter bekannt, die in den meisten Anwendung der Navigation und Orientierungsbestimmungen von Flugzeugen zum Einsatz kommt.

https://creativecommons.org/licenses/by-sa/4.0/
about this event: https://c3voc.de
</description>
      <enclosure url="https://cdn.media.ccc.de/contributors/realraum/h264-hd/realraum-56371-deu-Kalman_Filter_und_Sensor_Fusion_hd.mp4"
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      <pubDate>Thu, 25 Sep 2025 19:15:00 +0200</pubDate>
      <guid isPermaLink="true">https://cdn.media.ccc.de/contributors/realraum/h264-hd/realraum-56371-deu-Kalman_Filter_und_Sensor_Fusion_hd.mp4?1758883514</guid>
      <dc:identifier>3dfa1cff-44d5-43c9-ac1c-9d72a0beaba7</dc:identifier>
      <dc:date>2025-09-25T19:15:00+02:00</dc:date>
      <itunes:author>Christian Hartler</itunes:author>
      <itunes:explicit>No</itunes:explicit>
      <itunes:keywords>56371, 2025, realraum, LoTHR, realraum-deu, realraum, r3, r3talks, graz, Day 3</itunes:keywords>
      <itunes:summary>Ein kurzer Vortrag, der die Vor- und Nachteile einzelner Sensoren aufzeigt, was die Entwicklung der Sensor Fusion motivierte. Es wird ein Überblick geschaffen, wie man vom einfachen Complementary Filter zum Kalman Filter kommt und wie man diesen adaptiert um nichtlineare Zustände zu berechnen. Diese Erweiterung ist als Extended Kalman Filter bekannt, die in den meisten Anwendung der Navigation und Orientierungsbestimmungen von Flugzeugen zum Einsatz kommt.

https://creativecommons.org/licenses/by-sa/4.0/
about this event: https://c3voc.de
</itunes:summary>
      <itunes:duration>00:31:07</itunes:duration>
      <itunes:image href="https://static.media.ccc.de/media/contributors/realraum/56371-3dfa1cff-44d5-43c9-ac1c-9d72a0beaba7.jpg"/>
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      <title>DIY Revival of an API 2000 Tandem Mass Spectrometer (realraum)</title>
      <link>https://media.ccc.de/v/realraum-56370-diy-revival-of-an-api-200</link>
      <description>

Ever wondered if you could bring an old mass spectrometer back to life? Well, that’s exactly what this project was all about! With a mix of DIY repairs, scavenged parts, and a whole lot of learning, the API2000 tandem mass spectrometer got a second chance.

From fixing a corroded interface heater to tracking down the right software (hello, Windows XP nostalgia!), every step was a challenge. But in the end, the first tests were a success – including injecting coffee to confirm the presence of caffeine (because, of course, coffee had to be involved).

The journey doesn’t stop here. Next steps? Diving into deeper mathematical concepts, experimenting with blood analysis, and pushing the API2000 to its limits.
about this event: https://gry.sh/posts/dgms2025/
</description>
      <enclosure url="https://cdn.media.ccc.de/contributors/realraum/h264-hd/import-56370-eng-DIY_Revival_of_an_API_2000_Tandem_Mass_Spectrometer_hd.mp4"
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      <pubDate>Fri, 04 Apr 2025 21:00:00 +0200</pubDate>
      <guid isPermaLink="true">https://cdn.media.ccc.de/contributors/realraum/h264-hd/import-56370-eng-DIY_Revival_of_an_API_2000_Tandem_Mass_Spectrometer_hd.mp4?1757065350</guid>
      <dc:identifier>6b097c7a-c3cf-44da-bb53-aaa103deff9e</dc:identifier>
      <dc:date>2025-04-04T21:00:00+02:00</dc:date>
      <itunes:author>Sally</itunes:author>
      <itunes:explicit>No</itunes:explicit>
      <itunes:keywords>56370, 2025, realraum, LoTHR, realraum-eng</itunes:keywords>
      <itunes:summary>

Ever wondered if you could bring an old mass spectrometer back to life? Well, that’s exactly what this project was all about! With a mix of DIY repairs, scavenged parts, and a whole lot of learning, the API2000 tandem mass spectrometer got a second chance.

From fixing a corroded interface heater to tracking down the right software (hello, Windows XP nostalgia!), every step was a challenge. But in the end, the first tests were a success – including injecting coffee to confirm the presence of caffeine (because, of course, coffee had to be involved).

The journey doesn’t stop here. Next steps? Diving into deeper mathematical concepts, experimenting with blood analysis, and pushing the API2000 to its limits.
about this event: https://gry.sh/posts/dgms2025/
</itunes:summary>
      <itunes:duration>02:07:43</itunes:duration>
      <itunes:image href="https://static.media.ccc.de/media/contributors/realraum/56370-6b097c7a-c3cf-44da-bb53-aaa103deff9e.jpg"/>
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      <itunes:name>CCC media team</itunes:name>
      <itunes:email>media@c3voc.de</itunes:email>
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    <itunes:author>CCC media team</itunes:author>
    <itunes:explicit>No</itunes:explicit>
    <itunes:keywords>CCC Congress Hacking Security Netzpolitik</itunes:keywords>
    <itunes:subtitle>A wide variety of video material distributed by the CCC. All content is taken from cdn.media.ccc.de and media.ccc.de</itunes:subtitle>
    <itunes:summary>A wide variety of video material distributed by the Chaos Computer Club. This feed contains all events from realraum as mp4</itunes:summary>
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