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<!DOCTYPE HTML>
<html><!-- this is the code page -->
<head>
<title>Code</title>
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<h2>Code </h2>
<i>This page contains links to code for some recent projects from the Yu group (see specific papers for other code repositories). Going forward, code will be added to the <a href="https://github.com/Yu-Group">Yu-group github</a>.</i>
</center>
</br>
<h3 id="data-science-libraries"> <strong> <a href="#data-science-libraries">Multipurpose data-science libraries</a> </strong> </h3>
<ul>
</a> </li> </br>
<li><a href="https://github.com/Yu-Group/pcs-pipeline">VeridicalFlow🚰: a library for building stable, trustworthy data-science pipelines based on the PCS framework</a> </li> </br>
<li><a href="https://github.com/Yu-Group/simChef">simChef 🍳: An R package to facilitate PCS simulation studies</a> </li> </br>
<li><a href="https://github.com/csinva/imodels">imodels 🔎: a python package for fitting interpretable models</a></li></br>
<ul style="list-style-type: disc; padding-left: 5%">
<li>FIGS (<a href="https://arxiv.org/abs/2201.11931">preprint</a>, <a href="https://csinva.io/imodels/tree/figs.html">docs</a>)</li>
<li>Hierarchical shrinkage (<a href="https://proceedings.mlr.press/v162/agarwal22b.html">paper</a>, <a href="https://csinva.io/imodels/tree/hierarchical_shrinkage.html">docs</a>)</li>
<li>MDI+ (<a href="https://arxiv.org/pdf/2307.01932.pdf">preprint</a>, <a href="https://csinva.io/imodels/importance/mdi_plus.html">docs</a>)</li>
</ul>
</ul>
<h3 id="stable-modeling"> <strong> <a href="#stable-modeling">Stable modeling</a> </strong> </h3>
<ul>
<li>iRF: iterative Random Forests (<a href="https://github.com/Yu-Group/iterative-Random-Forest">Python package</a>, <a href="https://github.com/karlkumbier/iRF2.0">R package</a>) (PCS-guided) </li> </br>
<ul style="list-style-type: disc; padding-left: 5%">
<li>siRF (<a href="https://github.com/karlkumbier/iRF2.0">GitHub code repository</a>)</li>
<li>lo-siRF (<a href="https://github.com/Yu-Group/epistasis-cardiac-hypertrophy">GitHub code repository</a>)</li>
</ul>
<li><a href="https://www.rdocumentation.org/packages/hdci/versions/1.0-2/topics/escv.glmnet">escv selection of regularization for lasso for sparser and more interpretable models.</a> (<a href="https://www.tandfonline.com/doi/abs/10.1080/10618600.2015.1020159">paper</a>) (first work related to PCS) </li></br>
<li><a href="https://github.com/yu-group/stanmf">stanmf: stability driven non-negative matrix factorization</a> (PCS-guided)</li></br>
<li>Causal inference: <a href="https://github.com/soerenkuenzel/hte">X-learner: CATE prediction</a>, <a href="https://github.com/Yu-Group/stadisc"> staDISC: discovering stable subgroups</a> (PCS-guided) </li> </br>
</ul>
<h3 id="interpretation-visualization"> <strong> <a href="#interpretation-visualization"> Interpretation / Visualization </a> </strong> </h3>
<ul>
<li>Interpreting neural networks 🧠: <a href="https://github.com/csinva/acd">ACD: hierarchical interpretations</a>, <a href="https://github.com/csinva/transformation-importance"> TRIM: interpreting transformations</a>, <a href="https://github.com/laura-rieger/deep-explanation-penalization"> CDEP: penalizing explanations </a> </li> </br>
<li>Adaptive wavelets 🌊: <a href="https://github.com/Yu-Group/adaptive-wavelets">AWD: adaptive wavelets and wavelet distillation</a></li> </br>
<li>Visualization 🔥: <a href="https://rlbarter.github.io/superheat/">Superheat: An r package for generating beautiful and customizable heatmaps</a> </li> </br>
</ul>
<ul>
<h3 id="applied-projects"> <strong> <a href="#applied-projects"> Applied projects </a> </strong> </h3>
<li>Epistasis regulates genetic control of cardiac hypertrophy: <a href="https://www.medrxiv.org/content/10.1101/2023.11.06.23297858v1">preprint</a>, <a href="https://github.com/Yu-Group/epistasis-cardiac-hypertrophy">GitHub code repository</a>, <a href="https://yu-group.github.io/epistasis-cardiac-hypertrophy/#overview">PCS documentation</a> (PCS-guided) </li></br>
<li><a href="https://github.com/merlebehr/epiTree">epiTree — Learning epistatic polygenic phenotypes with boolean interactions</a> (PCS inference)</li></br>
<li><a href="https://github.com/Yu-Group/covid19-severity-prediction">Extensive and accessible COVID-19 data + forecasting at the county-level + hospital-level. </a> </li></br>
<li><a href="https://github.com/Yu-Group/staDRIP">staDRIP: drug-response prediction</a> (PCS-guided) </li>
</br>
</ul>
<h3 id="theory"> <strong> <a href="#theory"> Theory </a> </strong> </h3>
<ul>
<li><a href="https://github.com/shifwang/paper-debiased-feature-importance">MDI OOB: Debiased RF feature importance</a></li></br>
<li><a href="https://github.com/csinva/mdl-complexity">MDL-Complexity</a> </li> </br>
</ul>
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