<div dir="ltr"><div class="gmail-group-header" style="box-sizing:inherit;font-family:Mallory,Verdana,Arial,Helvetica,sans-serif;font-size:17px"><span class="gmail-field gmail-field-name-title gmail-field-type-ds gmail-field-label-hidden" style="box-sizing:inherit"><span style="box-sizing:inherit"><span class="gmail-odd gmail-first gmail-last" style="box-sizing:inherit"><h1 class="gmail-title" style="box-sizing:inherit;font-weight:300;padding:0px;font-feature-settings:"kern","liga","dlig";font-size:1.76471em;line-height:normal;font-stretch:normal;color:rgb(0,60,118);text-transform:uppercase;display:inline-block">YIXIN WANG</h1></span></span></span>, <span class="gmail-field gmail-field-name-field-university gmail-field-type-text gmail-field-label-hidden" style="box-sizing:inherit;margin-left:5px"><span style="box-sizing:inherit"><span class="gmail-odd gmail-first gmail-last" style="box-sizing:inherit">Columbia University</span></span></span><div class="gmail-field gmail-field-name-field-abstract-title gmail-field-type-text gmail-field-label-hidden" style="box-sizing:inherit"><div class="gmail-field-items" style="box-sizing:inherit"><div class="gmail-field-item even" style="box-sizing:inherit;font-size:20px;font-weight:600;line-height:1.2;margin-bottom:1em;margin-top:0.5em">The Blessings of Multiple Causes</div></div></div></div><div class="gmail-group-left" style="box-sizing:inherit;float:left;width:auto;padding-right:14.4844px;max-width:30%;font-family:Mallory,Verdana,Arial,Helvetica,sans-serif;font-size:17px"><div class="gmail-field gmail-field-name-field-image gmail-field-type-image gmail-field-label-hidden" style="box-sizing:inherit"><div class="gmail-field-items" style="box-sizing:inherit"><div class="gmail-field-item even" style="box-sizing:inherit"><img src="https://statistics.yale.edu/sites/default/files/styles/user_picture_node/public/img-profile.png?itok=0PLFvkwo" width="400" height="480" alt="" style="box-sizing: inherit; border: 0px; max-width: 100%; height: auto; vertical-align: bottom;"></div></div></div></div><div class="gmail-group-right" style="box-sizing:inherit;float:left;width:auto;max-width:65%;padding-left:21.7344px;font-family:Mallory,Verdana,Arial,Helvetica,sans-serif;font-size:17px"><div class="gmail-field gmail-field-name-field-event-time gmail-field-type-datetime gmail-field-label-hidden" style="box-sizing:inherit"><div class="gmail-field-items" style="box-sizing:inherit"><div class="gmail-field-item even" style="box-sizing:inherit;color:rgb(0,60,118);font-size:18px;line-height:1.4"><span class="gmail-date-display-single" style="box-sizing:inherit">Monday, February 17, 2020<span class="gmail-date-display-range" style="box-sizing:inherit;float:left;width:392.422px"><span class="gmail-date-display-start" style="box-sizing:inherit">4:00PM</span> to <span class="gmail-date-display-end" style="box-sizing:inherit">5:00PM</span></span></span></div></div></div><div class="gmail-field gmail-field-name-field-location gmail-field-type-location gmail-field-label-hidden" style="box-sizing:inherit"><div class="gmail-field-items" style="box-sizing:inherit"><div class="gmail-field-item even" style="box-sizing:inherit"><div class="gmail-location gmail-vcard" style="box-sizing:inherit"><div class="gmail-adr" style="box-sizing:inherit"><span class="gmail-fn" style="box-sizing:inherit">YINS</span> <span class="gmail-map-icon" style="box-sizing:inherit;margin-left:0.25em;font-size:0.925em;line-height:1.55;letter-spacing:0.05em;word-spacing:0.05em;text-transform:lowercase;font-feature-settings:"smcp""><a href="http://maps.google.com/?q=17+Hillhouse+Avenue%2C+Rm.+328%2C+New+Haven%2C+CT%2C+06511%2C+us" style="box-sizing:inherit;outline:none;line-height:inherit;color:rgb(40,109,192)">see map</a> </span><div class="gmail-street-address" style="box-sizing:inherit">17 Hillhouse Avenue, Rm. 328</div><span class="gmail-locality" style="box-sizing:inherit">New Haven</span>, <span class="gmail-region" style="box-sizing:inherit">CT</span> <span class="gmail-postal-code" style="box-sizing:inherit">06511</span></div></div></div></div></div><div class="gmail-field gmail-field-name-field-website gmail-field-type-link-field gmail-field-label-hidden" style="box-sizing:inherit"><div class="gmail-field-items" style="box-sizing:inherit"><div class="gmail-field-item even" style="box-sizing:inherit"><a href="http://www.stat.columbia.edu/~yixinwang/" style="box-sizing:inherit;text-decoration-line:none;outline:none;line-height:1.5;color:rgb(0,60,118);font-size:16px">Website</a></div></div></div></div><div class="gmail-group-footer" style="box-sizing:inherit;clear:both;padding-top:15px;font-family:Mallory,Verdana,Arial,Helvetica,sans-serif;font-size:17px"><div class="gmail-field gmail-field-name-body gmail-field-type-text-with-summary gmail-field-label-above" style="box-sizing:inherit"><div class="gmail-field-label" style="box-sizing:inherit;font-weight:bold">Information and Abstract: </div><div class="gmail-field-items" style="box-sizing:inherit"><div class="gmail-field-item even" style="box-sizing:inherit"><p style="box-sizing:inherit;margin:0px 0px 1em;padding:0px">Causal inference from observational data is a vital problem, but it comes with strong assumptions. Most methods assume that we observe all confounders, variables that affect both the causal variables and the outcome variables. But whether we have observed all confounders is a famously untestable assumption. We describe the deconfounder, a way to do causal inference from observational data allowing for unobserved confounding.</p><p style="box-sizing:inherit;margin:0px 0px 1em;padding:0px">How does the deconfounder work? The deconfounder is designed for problems of multiple causal inferences: scientific studies that involve many causes whose effects are simultaneously of interest. The deconfounder uses the correlation among causes as evidence for unobserved confounders, combining unsupervised machine learning and predictive model checking to perform causal inference. We study the theoretical requirements for the deconfounder to provide unbiased causal estimates, along with its limitations and tradeoffs. We demonstrate the deconfounder on real-world data and simulation studies.</p></div></div></div></div></div>