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<p class="MsoNormal"><span lang="EN-US" style="font-size:14.0pt">Welcome to an IDA Machine Learning Seminar on Wednesday, April 19 at 15:15 in Ada Lovelace<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US"><o:p> </o:p></span></p>
<p class="MsoNormal"><b><span lang="EN-US" style="font-size:16.0pt;color:black">AI4Science at Microsoft Research</span></b><b><span lang="EN-US" style="font-size:14.0pt;color:black"><br>
</span></b><b><span style="font-size:14.0pt;color:black"><a href="https://www.microsoft.com/en-us/research/people/rvandenberg/"><span lang="EN-US" style="color:#225785;text-decoration:none">Rianne van den Berg</span></a></span></b><b><span lang="EN-US" style="font-size:14.0pt;color:black">,
Principal Researcher, Microsoft Research Amsterdam<o:p></o:p></span></b></p>
<p class="MsoNormal"><b><span lang="EN-US" style="font-size:8.5pt;font-family:"Verdana",sans-serif;color:black"><o:p> </o:p></span></b></p>
<p class="MsoNormal"><i><span lang="EN-US">Abstract:</span></i><span lang="EN-US"> In July 2022 Microsoft announced a new global team in Microsoft Research, spanning the UK, China and the Netherlands, to focus on AI for science. In September 2022 we announced
that we have also opened a new lab in Berlin, Germany, and recently another team in Redmond (USA) joined our initiative. In this talk I will first discuss some of the research areas that we are currently exploring in AI4Science at Microsoft Research, covering
topics such as drug discovery, material generation, neural PDE solvers, electronic structure theory. Then I will dive a little deeper into two recent works that were done at AI4Science. First, I will cover work on the use of score-based generative modeling
for coarse-graining (CG) molecular dynamics simulations. By training a diffusion model on protein structures from molecular dynamics simulations we show that its score function approximates a force field that can directly be used to simulate CG molecular dynamics.
While having a vastly simplified training setup compared to previous work, we demonstrate that our approach leads to improved performance across several small- to medium-sized protein simulations, reproducing the CG equilibrium distribution, and preserving
dynamics of all-atom simulations such as protein folding events. Second, I will discuss our recent work on Clifford Neural layers for PDE modeling. The PDEs of many physical processes describe the evolution of scalar and vector fields. In order to take into
account the correlation between these different fields and their internal components, we represent these fields as multivectors, which consist of scalar, vector, as well as higher-order components. Their algebraic properties, such as multiplication, addition
and other arithmetic operations can be described by Clifford algebras, which we use to design Clifford convolutions and Clifford Fourier transforms. We empirically evaluate the benefit of Clifford neural layers by replacing convolution and Fourier operations
in common neural PDE surrogates by their Clifford counterparts on two-dimensional Navier-Stokes and weather modeling tasks, as well as three-dimensional Maxwell equations.<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US"><o:p> </o:p></span></p>
<p class="MsoNormal"><span lang="EN-US">Location: <b>Ada Lovelace,</b> <a href="https://www.ida.liu.se/department/location/search.en.shtml?keyword=ada">
https://www.ida.liu.se/department/location/search.en.shtml?keyword=ada</a><o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US">Organizers: Fredrik Lindsten, Sourabh Balgi<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US"><o:p> </o:p></span></p>
<p class="MsoNormal">------------------<o:p></o:p></p>
<p class="MsoNormal"> <o:p></o:p></p>
<p class="MsoNormal"><span lang="EN-US">The list of future seminars in the series is available at:
</span><a href="http://www.ida.liu.se/research/machinelearning/seminars/" target="_BLANK"><span lang="EN-US">http://www.ida.liu.se/research/machinelearning/seminars/</span></a><span lang="EN-US"><o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US">You can subscribe to the seminar series' calendar using this ics link:
<a href="https://outlook.office365.com/owa/calendar/4d811ae47ce446f58d11a7c2f50a7ed8@ad.liu.se/0f5253d7bc7841248c71eb4c28eb2d668927992292494627279/calendar.ics" target="_BLANK">
https://outlook.office365.com/owa/calendar/4d811ae47ce446f58d11a7c2f50a7ed8@ad.liu.se/0f5253d7bc7841248c71eb4c28eb2d668927992292494627279/calendar.ics</a><o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US"> <o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US">Welcome!<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US">IDA Machine Learning Group<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US">Linköping University<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US"><o:p> </o:p></span></p>
<p class="MsoNormal"><span lang="EN-US"><o:p> </o:p></span></p>
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