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    <title>Matt Broerman</title>
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    <description>Recent content on Matt Broerman</description>
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      <title>Yes, but what are Gaussian Processes?</title>
      <link>/2020/12/03/but-what-are-gps/</link>
      <pubDate>Thu, 03 Dec 2020 00:00:00 +0000</pubDate>
      
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      <description>Part I of a conceptual introduction to Gaussian processes, focusing on understanding GPs as stochastic processes.</description>
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      <title>Modeling Seasonal Variation in Fuel Consumption</title>
      <link>/2020/11/13/pa-plant-carbon-part-2/</link>
      <pubDate>Fri, 13 Nov 2020 00:00:00 +0000</pubDate>
      
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      <description>Simple time series model of fuel comsumption at power plants.</description>
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      <title>How Much Carbon Do Pennsylvania Electricity Plants Emit?</title>
      <link>/2020/11/12/pa-plant-carbon-part-1/</link>
      <pubDate>Thu, 12 Nov 2020 00:00:00 +0000</pubDate>
      
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      <description>EDA on electricity plants in Pennsylvania using the tidyverse and the eia package.</description>
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      <title>About</title>
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      <description>Hi, I&amp;rsquo;m Matt.
I recently graduated from the University of Pittsburgh with a Master in Applied Statistics. I got to work on some exciting projects in computational biology, I&amp;rsquo;m currently working on some collaborations with others, and I&amp;rsquo;m looking to work on some more. Please drop me a line at matt dot broerman at gmail dott com. Résumé available upon request.
Here I&amp;rsquo;ll be blogging mostly with R and Python about my interests in climate, the justice system, and bayesian methods, with some tips, reflections, and art along the way.</description>
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      <title>License</title>
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      <pubDate>Thu, 05 May 2016 21:48:51 -0700</pubDate>
      
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      <description>All code appearing on this blog is licensed under MIT unless otherwise specified.
MIT License
Copyright (c) 2020 matt.broerman@gmail.com
Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the “Software”), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:</description>
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      <title>Projects</title>
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      <description>Interpretable factors in scRNA-seq with disentangled generative models New microfluidic platforms have enabled bioinformatics at an unprecedented level of resolution for single cells, but interpreting these vast arrays poses new challenges. Principle component analysis is a common tool for dimension reduction and interpretation, but does not perform well in this context due to nonlinear coordination between genes. I helped develop a method that has it both ways, modelling nonlinearities with variational autoencoders while remaining interpretable.</description>
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