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<p class="MsoNormal"><span lang="EN-US">Welcome to an on-site IDA Machine Learning Seminar on
<b>May 4, 15:15-16:15</b><o:p></o:p></span></p>
<p class="MsoNormal"><b><span lang="EN-US"><o:p> </o:p></span></b></p>
<p class="MsoNormal"><b><span lang="EN-US">Heiko Zimmermann,</span></b><span lang="EN-US"> Amsterdam Machine Learning Lab (AMLab), University of Amsterdam<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US"><a href="https://heikozimmermann.com/">https://heikozimmermann.com/</a><o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US"><o:p> </o:p></span></p>
<p class="MsoNormal"><b><span lang="EN-US">Learning Proposals for Probabilistic Programs with Inference Combinators<o:p></o:p></span></b></p>
<p class="MsoNormal"><i><span lang="EN-US">Abstract:</span></i><span lang="EN-US"> We develop operators for construction of proposals in probabilistic programs, which we refer to as inference combinators. Inference combinators define a grammar over importance
samplers that compose primitive operations such as application of a transition kernel and importance resampling. Proposals in these samplers can be parameterized using neural networks, which in turn can be trained by optimizing variational objectives. The
result is a framework for user-programmable variational methods that are correct by construction and can be tailored to specific models. We demonstrate the flexibility of this framework by implementing advanced variational methods based on amortized Gibbs
sampling and annealing.<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US"><o:p> </o:p></span></p>
<p class="MsoNormal"><span lang="EN-US">Paper: </span><a href="https://arxiv.org/pdf/2103.00668.pdf"><span lang="EN-US">https://arxiv.org/pdf/2103.00668.pdf</span></a><span lang="EN-US"><o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US"><o:p> </o:p></span></p>
<p class="MsoNormal"><b><span lang="EN-US">Location:</span></b><span lang="EN-US"> Alan Turing, House E,
<a href="https://www.ida.liu.se/department/location/search.en.shtml?keyword=alan">
https://www.ida.liu.se/department/location/search.en.shtml?keyword=alan</a><o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US"><o:p> </o:p></span></p>
<p class="MsoNormal"><span lang="EN-US"><o:p> </o:p></span></p>
<p class="MsoNormal"><span lang="EN-US">Welcome!<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US">IDA Machine Learning Group<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US">Linköping University<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US"><o:p> </o:p></span></p>
<p class="MsoNormal"><span lang="EN-US">PS. I can also take the opportunity to remind everyone about the seminar this Wednesday 2/4 at 15:15 by
<b>Çağatay Yıldız</b>. This seminar will be over Zoom, <a href="https://liu-se.zoom.us/j/69011766298">
https://liu-se.zoom.us/j/69011766298</a><o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US"><o:p> </o:p></span></p>
<p class="MsoNormal"><span lang="EN-US"><o:p> </o:p></span></p>
<p class="MsoNormal"><span lang="EN-US">-------<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US">The list of future seminars in the series is available at:
</span><a href="http://www.ida.liu.se/research/machinelearning/seminars/"><span lang="EN-US">http://www.ida.liu.se/research/machinelearning/seminars/</span></a><span lang="EN-US">.<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US">You can subscribe to the seminar series' calendar using this ics link:
<a href="https://outlook.office365.com/owa/calendar/4d811ae47ce446f58d11a7c2f50a7ed8@ad.liu.se/0f5253d7bc7841248c71eb4c28eb2d668927992292494627279/calendar.ics">
https://outlook.office365.com/owa/calendar/4d811ae47ce446f58d11a7c2f50a7ed8@ad.liu.se/0f5253d7bc7841248c71eb4c28eb2d668927992292494627279/calendar.ics</a><o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="mso-fareast-language:EN-US"><o:p> </o:p></span></p>
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