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JMLR<p>&#39;Improving Graph Neural Networks on Multi-node Tasks with the Labeling Trick&#39;, by Xiyuan Wang, Pan Li, Muhan Zhang.</p><p><a href="http://jmlr.org/papers/v26/23-0560.html" target="_blank" rel="nofollow noopener" translate="no"><span class="invisible">http://</span><span class="ellipsis">jmlr.org/papers/v26/23-0560.ht</span><span class="invisible">ml</span></a> <br /> <br /><a href="https://sigmoid.social/tags/subgraph" class="mention hashtag" rel="tag">#<span>subgraph</span></a> <a href="https://sigmoid.social/tags/nodes" class="mention hashtag" rel="tag">#<span>nodes</span></a> <a href="https://sigmoid.social/tags/hypergraphs" class="mention hashtag" rel="tag">#<span>hypergraphs</span></a></p>
Kevin Karhan :verified:<p><span class="h-card" translate="no"><a href="https://musician.social/@soulexpress" class="u-url mention" rel="nofollow noopener" target="_blank">@<span>soulexpress</span></a></span> <em>nodds in agreement</em> </p><ul><li>EVERY SINGLE ONE OF THEM!</li></ul><p>Like there's a reason I only got a copy of <a href="https://infosec.space/tags/SubgraphOS" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>SubgraphOS</span></a> as <em>non-public alpha</em> under the precondition to <em>not redistribute</em> and was allowed to <a href="https://www.youtube.com/watch?v=AAdzyCQdxvE" rel="nofollow noopener" target="_blank">preview it</a> because that thing was unstable and had a lot of <em>known issues</em> the devs were working on to get fixed.</p><ul><li>It's not as if they weren't aware of those, but they also didn't want <em>"<a href="https://infosec.space/tags/TechIlliterates" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>TechIlliterates</span></a>"</em> using it with a false belief in it being ready to use and trust in.</li></ul><p>Not shure how <a href="https://infosec.space/tags/Subgraph" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Subgraph</span></a> evolved after <a href="https://infosec.space/tags/grsecurity" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>grsecurity</span></a> decided to <a href="https://infosec.space/tags/paywall" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>paywall</span></a> access to the <a href="https://infosec.space/tags/sourcecodes" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>sourcecodes</span></a> of said <a href="https://infosec.space/tags/patches" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>patches</span></a> and <a href="https://infosec.space/tags/tools" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>tools</span></a> cuz those were used in said distro as a means to harden it.</p><ul><li>But then again the <a href="https://infosec.space/tags/grsec" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>grsec</span></a> devs seem to be so toxic, their entire Wikipedia Article got nuked and only an old <a href="https://web.archive.org/web/20200201055409/https://en.wikipedia.org/wiki/grsecurity" rel="nofollow noopener" target="_blank">archive version</a> exists.</li></ul>
JMLR<p>&#39;Random Subgraph Detection Using Queries&#39;, by Wasim Huleihel, Arya Mazumdar, Soumyabrata Pal.</p><p><a href="http://jmlr.org/papers/v25/22-0395.html" target="_blank" rel="nofollow noopener" translate="no"><span class="invisible">http://</span><span class="ellipsis">jmlr.org/papers/v25/22-0395.ht</span><span class="invisible">ml</span></a> <br /> <br /><a href="https://sigmoid.social/tags/subgraph" class="mention hashtag" rel="tag">#<span>subgraph</span></a> <a href="https://sigmoid.social/tags/graph" class="mention hashtag" rel="tag">#<span>graph</span></a> <a href="https://sigmoid.social/tags/algorithms" class="mention hashtag" rel="tag">#<span>algorithms</span></a></p>
Christian Boulanger<p><span class="h-card" translate="no"><a href="https://openbiblio.social/@librerli" class="u-url mention" rel="nofollow noopener" target="_blank">@<span>librerli</span></a></span> <span class="h-card" translate="no"><a href="https://openbiblio.social/@andreaswalker" class="u-url mention" rel="nofollow noopener" target="_blank">@<span>andreaswalker</span></a></span> I joined the WikiData telegram channel - but maybe the question I asked there is also something worth discussing here: how do I best export a <a href="https://sciences.social/tags/subgraph" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>subgraph</span></a> from <a href="https://sciences.social/tags/wikidata" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>wikidata</span></a> to edit it for later re-import? Is that something people (should) do? If yes, what tools are best suited for the purpose? I looked at <a href="https://neo4j.com/labs/neosemantics/how-to-guide/" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">neo4j.com/labs/neosemantics/ho</span><span class="invisible">w-to-guide/</span></a> because I am familiar with <a href="https://sciences.social/tags/Neo4J" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Neo4J</span></a>, but I obviously don't know if that's the right path...</p>
Published papers at TMLR<p>Subgraph Permutation Equivariant Networks</p><p>Joshua Mitton, Roderick Murray-Smith</p><p>Action editor: Guillaume Rabusseau.</p><p><a href="https://openreview.net/forum?id=3agxS3aDUs" target="_blank" rel="nofollow noopener" translate="no"><span class="invisible">https://</span><span class="ellipsis">openreview.net/forum?id=3agxS3</span><span class="invisible">aDUs</span></a></p><p><a href="https://sigmoid.social/tags/subgraph" class="mention hashtag" rel="tag">#<span>subgraph</span></a> <a href="https://sigmoid.social/tags/graphs" class="mention hashtag" rel="tag">#<span>graphs</span></a> <a href="https://sigmoid.social/tags/graph" class="mention hashtag" rel="tag">#<span>graph</span></a></p>
Published papers at TMLR<p>You Only Transfer What You Share: Intersection-Induced Graph Transfer Learning for Link Prediction</p><p>Wenqing Zheng, Edward W Huang, Nikhil Rao, Zhangyang Wang, Karthik Subbian</p><p>Action editor: Bo Han.</p><p><a href="https://openreview.net/forum?id=Nn71AdKyYH" target="_blank" rel="nofollow noopener" translate="no"><span class="invisible">https://</span><span class="ellipsis">openreview.net/forum?id=Nn71Ad</span><span class="invisible">KyYH</span></a></p><p><a href="https://sigmoid.social/tags/subgraph" class="mention hashtag" rel="tag">#<span>subgraph</span></a> <a href="https://sigmoid.social/tags/graphs" class="mention hashtag" rel="tag">#<span>graphs</span></a> <a href="https://sigmoid.social/tags/nodes" class="mention hashtag" rel="tag">#<span>nodes</span></a></p>
JMLR<p>&#39;Quantifying Network Similarity using Graph Cumulants&#39;, by Gecia Bravo-Hermsdorff, Lee M. Gunderson, Pierre-André Maugis, Carey E. Priebe.</p><p><a href="http://jmlr.org/papers/v24/21-082.html" target="_blank" rel="nofollow noopener" translate="no"><span class="invisible">http://</span><span class="">jmlr.org/papers/v24/21-082.html</span><span class="invisible"></span></a> <br /> <br /><a href="https://sigmoid.social/tags/subgraph" class="mention hashtag" rel="tag">#<span>subgraph</span></a> <a href="https://sigmoid.social/tags/graph" class="mention hashtag" rel="tag">#<span>graph</span></a> <a href="https://sigmoid.social/tags/similarity" class="mention hashtag" rel="tag">#<span>similarity</span></a></p>
New Submissions to TMLR<p>Unlock the Black Box by Interpreting Graph Convolutional Networks via Additive Decomposition</p><p><a href="https://openreview.net/forum?id=sroF8hhbzW" target="_blank" rel="nofollow noopener" translate="no"><span class="invisible">https://</span><span class="ellipsis">openreview.net/forum?id=sroF8h</span><span class="invisible">hbzW</span></a></p><p><a href="https://sigmoid.social/tags/gnn" class="mention hashtag" rel="tag">#<span>gnn</span></a> <a href="https://sigmoid.social/tags/subgraph" class="mention hashtag" rel="tag">#<span>subgraph</span></a> <a href="https://sigmoid.social/tags/interpretability" class="mention hashtag" rel="tag">#<span>interpretability</span></a></p>
JMLR<p>&#39;Sampling random graph homomorphisms and applications to network data analysis&#39;, by Hanbaek Lyu, Facundo Memoli, David Sivakoff.</p><p><a href="http://jmlr.org/papers/v24/20-449.html" target="_blank" rel="nofollow noopener" translate="no"><span class="invisible">http://</span><span class="">jmlr.org/papers/v24/20-449.html</span><span class="invisible"></span></a> <br /> <br /><a href="https://sigmoid.social/tags/subgraph" class="mention hashtag" rel="tag">#<span>subgraph</span></a> <a href="https://sigmoid.social/tags/graphs" class="mention hashtag" rel="tag">#<span>graphs</span></a> <a href="https://sigmoid.social/tags/adjacency" class="mention hashtag" rel="tag">#<span>adjacency</span></a></p>