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Bump kramdown from 2.2.1 to 2.3.1 #2

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912832e
Update index.html
sgfin Jul 29, 2020
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sgfin Jul 29, 2020
9e99f20
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sgfin Jul 29, 2020
5310c5f
Bump kramdown from 2.2.1 to 2.3.1
dependabot[bot] Mar 30, 2021
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2 changes: 1 addition & 1 deletion Gemfile.lock
100755 → 100644
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Expand Up @@ -49,7 +49,7 @@ GEM
jekyll (~> 4.0)
jekyll-watch (2.2.1)
listen (~> 3.0)
kramdown (2.2.1)
kramdown (2.3.1)
rexml
kramdown-parser-gfm (1.1.0)
kramdown (~> 2.0)
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4 changes: 2 additions & 2 deletions index.html
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Expand Up @@ -83,7 +83,7 @@
<br><br>
In addition to my research, I am involved in the Hydrocephalus community by way of <a href="http://teamhydro.org">Team Hydro</a>, a non-profit organization that my family and I started to raise money and awareness for the condition in honor of my sister, <a href="http://teamhydro.org/kate-finlayson/">Kate</a>. I also do consulting work as a data scientist and deep learning engineer, with clients including tech, biotech, and pharmaceutical companies.
<br><br>
For a more formal account of my academic work, see my <a href=../assets/sgf_cv.pdf"> Curriculum Vitae</a> or <a href="https://scholar.google.com/citations?user=7__yMlEAAAAJ&hl=en">Google Scholar</a>.
For a more formal account of my academic work, see my <a href="../assets/sgf_cv.pdf"> Curriculum Vitae</a> or <a href="https://scholar.google.com/citations?user=7__yMlEAAAAJ&hl=en">Google Scholar</a>.
</p>
</div><!-- table container -->

Expand Down Expand Up @@ -140,7 +140,7 @@ <h3>Subgraph Neural Networks</h3>
<i>In Submission, 2020<br>
<i>*Co-first, listed alphabetically<br>
[<a class="showSingle", target="27">Abstract</a>]
[<a href="">Paper</a>]
[<a href="https://arxiv.org/abs/2006.10538">Paper</a>]
</p>
<div id="div27" class="abstract">
Deep learning methods for graphs achieve remarkable performance on many node-level and graph-level prediction tasks. However, despite the proliferation of the methods and their success, prevailing Graph Neural Networks (GNNs) neglect subgraphs, rendering subgraph prediction tasks challenging to tackle in many impactful applications. Further, subgraph prediction tasks present several unique challenges: subgraphs can have non-trivial internal topology, but also carry a notion of position and external connectivity information relative to the underlying graph in which they exist.
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