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<h2><a href="/bayesian-changepoint-detection-in-numpyro.html#bayesian-changepoint-detection-in-numpyro">Bayesian Changepoint Detection in (Num)Pyro</a></h2>
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Posted on Tue 08 June 2021 in <a href="/category/probabilistic-programming-changepoint-detection-bayesian.html">probabilistic programming, changepoint detection, Bayesian</a>
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<p>Chad Scherrer has a <a href="https://cscherrer.github.io/post/bayesian-changepoint/">blog post</a> about how to do Bayesian changepoint detection in PyMC3, in the context of detecting changepoint associated with the yearly number of coal mining disasters. Here we will see how to implement the same model in <a href="https://pyro.ai">Pyro</a>, a probabilistic programming language and environment using <a href="https://pytorch.org">PyTorch …</a></p>
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<h2><a href="/kolm-and-ritter-2018.html#kolm-and-ritter-2018">Kolm and Ritter (2018)</a></h2>
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Posted on Sat 12 October 2019 in <a href="/category/reinforcement-learning.html">reinforcement learning</a>
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<div class="highlight"><pre><span></span><code><span class="o">%</span><span class="n">reload_ext</span> <span class="n">autoreload</span>
<span class="o">%</span><span class="n">autoreload</span> <span class="mi">2</span>
<span class="o">%</span><span class="n">matplotlib</span> <span class="n">inline</span>
</code></pre></div>
<p>In an <a href="https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3281235">SSRN paper</a>, Petter Kolm and Gordon Ritter present the application of reinforcement learning for model-free European call option hedging. Unfortunately, there does not seem to be any code made available to accompany this paper. Here we try to replicate the results of …</p>
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<h2><a href="/migrating-to-pelican.html#migrating-to-pelican">Migrating to Pelican</a></h2>
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Posted on Sat 21 September 2019 in <a href="/category/misc.html">misc</a>
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<p>After some extended hiatus, trying to pick up writing this blog again. I have also decided to migrate to <a href="https://docs.getpelican.com/en/stable/">Pelican</a>.</p>
<p>I have found these resources to be useful during the migration:</p>
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<li><a href="https://rasor.github.io/using-pelican-blog-on-github-pages.html">rasor.github.io</a></li>
<li><a href="http://anotherdatum.com/pelican-and-github-pages-workflow.html">anotherdatum.com</a></li>
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<h2><a href="/performance-comparison-of-keras-examples-when-run-using-theano-and-tensorflow.html#performance-comparison-of-keras-examples-when-run-using-theano-and-tensorflow">Performance comparison of Keras examples when run using Theano and TensorFlow</a></h2>
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Posted on Sat 25 June 2016 in <a href="/category/deep-learning.html">deep learning</a>
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<p>Setup: 2x Xeon E5 2670, 128GB RAM, Nvidia Geforce GTX 980 Ti (6GB), Ubuntu 14.04, CUDA 7.5, Anaconda 4.0 running Python 2.7, Theano 0.8.2 (CNMem turned on), TensorFlow 0.9.0, CuDNN 4</p>
<p>Each time is time for the first epoch. There is also …</p>
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