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sciML.html

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<h1 id="scientific-machine-learning-mini-course">Scientific Machine Learning Webinar Series</h1>
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<h2 id="website-change" style="color:#ff0000"> The SciML webinar has moved to the University of Michigan's MICDE. Find the website, calendar,
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Zoom link and talks at <a href="https://micdedev.wpengine.com/news-events/sciml-webinar-series/">
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https://micdedev.wpengine.com/news-events/sciml-webinar-series/ </a>. If you were already on our mailing list, you
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do not have to sign up again.
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</h2>
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<br>
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<p>This webinar series and panel events are organized by <a href="https://www.andrew.cmu.edu/user/mphuthi/">Keith Phuthi</a>, Varun Shankar and <a href="https://www.andrew.cmu.edu/user/venkatv/">Venkat Viswanathan</a> with the goal of cross-pollinating ideas between the various emerging methods at the intersection of physics and machine learning.</p>
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<p>Webinar Format: Presenters can use the opportunity to showcase a paper or two with an explicit focus on the methodology and approach. Duration: 40 minutes of methodology + 20 minutes of implementation (code) walk-through + 20 minutes of questions. Invited session chairs will guide the discussion along with offering their perspective on the field. The Q&amp;A session is typically very interactive with a small group of enthusiastic audience.</p>
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<p>Seminar Time: Thursdays 11 am to 12:30 pm Eastern Time </p>
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<iframe src="https://calendar.google.com/calendar/embed?height=600&amp;wkst=1&amp;bgcolor=%23ffffff&amp;ctz=America%2FNew_York&amp;src=Y19pajU0dHVtbmM2OWV0YW9pbWFwODNzZmxzY0Bncm91cC5jYWxlbmRhci5nb29nbGUuY29t&amp;color=%23D50000" style="border:solid 1px #777" width="800" height="600" frameborder="0" scrolling="no"></iframe>
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<h2 id="How To Join">How To Join</h2>
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<!-- <h2 id="How To Join">How To Join</h2>
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<p><a href="https://calendar.google.com/calendar/u/0/r?cid=c_ij54tumnc69etaoimap83sflsc@group.calendar.google.com">Add Webinar Calendar</a><br />
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<a href="https://cmu.zoom.us/j/99244798052?pwd=dTlCYkpHK3kzdStEd3FuWWU5amJ4dz09">Zoom Link</a><br />
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Webinar ID: 992 4479 8052<br />
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Passcode: 919401</p>
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Passcode: 919401</p> -->
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<h4 id="How To Join">Suggest speakers: </h4>
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<p><a href="https://docs.google.com/forms/d/e/1FAIpQLSdv6yyHQ2XSfOOqNlG0QZRlDA11BItCz1wBTZmr16an9qx2LQ/viewform?usp=sf_link"> Form </a></p>
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<br/>
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<h2 id="tentative-speakers-and-topics">Upcoming/Ongoing Events</h2>
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<h2 id="tentative-speakers-and-topics"> Past Webinars </h2>
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<h4 id="ML-embed">Spring 2023:</h4>
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<ul>
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</li>
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</ul>
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<h2 id="past-speakers-and-topics">Past Webinars</h2>
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<h4 id="ML-embed">Fall 2022:</h4>
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<ul>
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<li>September 22: <a href="https://www.linkedin.com/in/ilyes-batatia-725ab5197/"> Batatia Ilyes (ENS Paris Saclay)</a>
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<h2 id="conception">Conception</h2>
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<p>A panel discussion on the topic <a href="https://pubs.acs.org/doi/full/10.1021/acsenergylett.8b02278">Machine Learning Based Approaches to Accelerate Energy Materials Discovery and Optimization</a> crystallized important considerations while applying machine learning methods to limited-data engineering applications. Often it's useful to synergistally stack the ML models to the extent possible with the known physics of the problem for effective learning even in low-data regimes.</p>
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<h2 id="questions">Questions?</h2>
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<p>Email the organizers at mphuthi[at]andrew.cmu.edu, varunshankar[at]cmu.edu and venkvis[at]cmu.edu</p>
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<p>Email the organizers at mkphuthi[at]cmu.edu and venkvis[at]cmu.edu</p>
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<h2 id="Video Recordings">Video Recordings</h2>
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A Google Drive link to the Video recordings are available on request on the slack or by emailing the organizers.
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#mc_embed_signup{background:#fff; clear:left; font:14px Helvetica,Arial,sans-serif; width:600px;}
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<div id="mce-responses" class="clear foot">
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</div> <!-- real people should not fill this in and expect good things - do not remove this or risk form bot signups-->
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</div>
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<div style="position: absolute; left: -5000px;" aria-hidden="true"><input type="text" name="b_d1019e4ff5e4e2b256b478eb1_cf9cef5736" tabindex="-1" value=""></div>
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<input type="submit" value="Subscribe" name="subscribe" id="mc-embedded-subscribe" class="button">
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</form>
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