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data-versiondate=&#034;2020-07-06T10:31:04+02:00&#034; href=&#034;https://github.com/facebookresearch/detectron2&#034; rel=&#034;nofollow&#034; class=&#034;description-link&#034;&gt;https://github.com/facebookresearch/detectron2&lt;/a&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/image"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/segmentation"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/network"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/cnn"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/deep"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/learning"/></rdf:Bag></taxo:topics></item><item rdf:about="https://graphdeeplearning.github.io/post/transformers-are-gnns/"><title>Transformers are Graph Neural Networks | NTU Graph Deep Learning Lab</title><description>Engineer friends often ask me: Graph Deep Learning sounds great, but are there any big commercial success stories? Is it being deployed in practical applications? Besides the obvious ones–recommendation systems at Pinterest, Alibaba and Twitter–a slightly nuanced success story is the Transformer architecture, which has taken the NLP industry by storm. Through this post, I want to establish links between Graph Neural Networks (GNNs) and Transformers. I’ll talk about the intuitions behind model architectures in the NLP and GNN communities, make connections using equations and figures, and discuss how we could work together to drive progress.</description><link>https://graphdeeplearning.github.io/post/transformers-are-gnns/</link><dc:creator>hotho</dc:creator><dc:date>2020-03-10T15:48:11+01:00</dc:date><dc:subject>deep graph learning network neural nn transformer </dc:subject><content:encoded>&lt;span itemprop=&#034;description&#034;&gt;Engineer friends often ask me: Graph Deep Learning sounds great, but are there any big commercial success stories? Is it being deployed in practical applications? Besides the obvious ones–recommendation systems at Pinterest, Alibaba and Twitter–a slightly nuanced success story is the Transformer architecture, which has taken the NLP industry by storm. Through this post, I want to establish links between Graph Neural Networks (GNNs) and Transformers. I’ll talk about the intuitions behind model architectures in the NLP and GNN communities, make connections using equations and figures, and discuss how we could work together to drive progress.&lt;/span&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/deep"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/graph"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/learning"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/network"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/neural"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/nn"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/transformer"/></rdf:Bag></taxo:topics></item><item rdf:about="http://enic.collide.info/"><title>Home | 4th European Network Intelligence Conference</title><description></description><link>http://enic.collide.info/</link><dc:creator>hotho</dc:creator><dc:date>2017-01-17T18:51:42+01:00</dc:date><dc:subject>2017 conference network pc recommender social </dc:subject><content:encoded>&lt;a itemprop=&#034;url&#034; data-versiondate=&#034;2017-01-17T18:51:42+01:00&#034; href=&#034;http://enic.collide.info/&#034; rel=&#034;nofollow&#034; class=&#034;description-link&#034;&gt;http://enic.collide.info/&lt;/a&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/2017"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/conference"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/network"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/pc"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/recommender"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/social"/></rdf:Bag></taxo:topics></item><item rdf:about="http://socialnetworks.mpi-sws.org/data-wosn2009.html"><title>Online Social Networks Research @ MPI-SWS</title><description></description><link>http://socialnetworks.mpi-sws.org/data-wosn2009.html</link><dc:creator>hotho</dc:creator><dc:date>2016-10-11T17:13:14+02:00</dc:date><dc:subject>dataset facebook link network </dc:subject><content:encoded>&lt;a itemprop=&#034;url&#034; data-versiondate=&#034;2016-10-11T17:13:14+02:00&#034; href=&#034;http://socialnetworks.mpi-sws.org/data-wosn2009.html&#034; rel=&#034;nofollow&#034; class=&#034;description-link&#034;&gt;http://socialnetworks.mpi-sws.org/data-wosn2009.html&lt;/a&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/dataset"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/facebook"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/link"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/network"/></rdf:Bag></taxo:topics></item><item rdf:about="http://karpathy.github.io/2015/05/21/rnn-effectiveness/"><title>The Unreasonable Effectiveness of Recurrent Neural Networks</title><description></description><link>http://karpathy.github.io/2015/05/21/rnn-effectiveness/</link><dc:creator>hotho</dc:creator><dc:date>2015-11-02T09:44:02+01:00</dc:date><dc:subject>deep learning network netze neural neuronale nn toread wj2017 </dc:subject><content:encoded>&lt;a itemprop=&#034;url&#034; data-versiondate=&#034;2015-11-02T09:44:02+01:00&#034; href=&#034;http://karpathy.github.io/2015/05/21/rnn-effectiveness/&#034; rel=&#034;nofollow&#034; class=&#034;description-link&#034;&gt;http://karpathy.github.io/2015/05/21/rnn-effectiveness/&lt;/a&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/deep"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/learning"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/network"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/netze"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/neural"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/neuronale"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/nn"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/toread"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/wj2017"/></rdf:Bag></taxo:topics></item><item rdf:about="https://opencorporates.com/viz/financial/"><title>OpenCorporates | How complex are corporate structures?</title><description></description><link>https://opencorporates.com/viz/financial/</link><dc:creator>hotho</dc:creator><dc:date>2014-11-04T12:33:23+01:00</dc:date><dc:subject>complex corporate network structures visualization </dc:subject><content:encoded>&lt;a itemprop=&#034;url&#034; data-versiondate=&#034;2014-11-04T12:33:23+01:00&#034; href=&#034;https://opencorporates.com/viz/financial/&#034; rel=&#034;nofollow&#034; class=&#034;description-link&#034;&gt;https://opencorporates.com/viz/financial/&lt;/a&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/complex"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/corporate"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/network"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/structures"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/visualization"/></rdf:Bag></taxo:topics></item><item rdf:about="http://ella.slis.indiana.edu/~katy/"><title>Katy Börner</title><description>Indiana University Professor specializing in scientometrics, informetrics, science of science studies, network science, cyberinfrastructure</description><link>http://ella.slis.indiana.edu/~katy/</link><dc:creator>hotho</dc:creator><dc:date>2013-04-24T11:12:56+02:00</dc:date><dc:subject>network research scholary science sota </dc:subject><content:encoded>&lt;span itemprop=&#034;description&#034;&gt;Indiana University Professor specializing in scientometrics, informetrics, science of science studies, network science, cyberinfrastructure&lt;/span&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/network"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/research"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/scholary"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/science"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/sota"/></rdf:Bag></taxo:topics></item><item rdf:about="http://research.microsoft.com/en-us/groups/apg/"><title>Applied Games - Microsoft Research</title><description>Our mission is to leverage the methods of machine learning and game theory for addressing relevant applications both in recreational games and in abstract decision games played in the real world.</description><link>http://research.microsoft.com/en-us/groups/apg/</link><dc:creator>hotho</dc:creator><dc:date>2012-03-19T16:36:26+01:00</dc:date><dc:subject>bayes elo games network prediction ranking research </dc:subject><content:encoded>&lt;span itemprop=&#034;description&#034;&gt;Our mission is to leverage the methods of machine learning and game theory for addressing relevant applications both in recreational games and in abstract decision games played in the real world.&lt;/span&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/bayes"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/elo"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/games"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/network"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/prediction"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/ranking"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/research"/></rdf:Bag></taxo:topics></item><item rdf:about="http://gephi.org/"><title>Gephi, an open source graph visualization and manipulation software</title><description>Gephi is an open-source software for visualizing and analyzing large networks graphs. Gephi uses a 3D render engine to display graphs in real-time and speed up the exploration. Use Gephi to explore, analyse, spatialise, filter, cluterize, manipulate and export all types of graphs.</description><link>http://gephi.org/</link><dc:creator>hotho</dc:creator><dc:date>2011-08-15T09:44:36+02:00</dc:date><dc:subject>analysis graph network sna visualization </dc:subject><content:encoded>&lt;span itemprop=&#034;description&#034;&gt;Gephi is an open-source software for visualizing and analyzing large networks graphs. Gephi uses a 3D render engine to display graphs in real-time and speed up the exploration. Use Gephi to explore, analyse, spatialise, filter, cluterize, manipulate and export all types of graphs.&lt;/span&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/analysis"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/graph"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/network"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/sna"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/visualization"/></rdf:Bag></taxo:topics></item><item rdf:about="http://www.iamresearcher.com/"><title>Welcome to iamResearcher</title><description></description><link>http://www.iamresearcher.com/</link><dc:creator>hotho</dc:creator><dc:date>2011-05-04T11:00:22+02:00</dc:date><dc:subject>network portal research researcher social </dc:subject><content:encoded>&lt;a itemprop=&#034;url&#034; data-versiondate=&#034;2011-05-04T11:00:22+02:00&#034; href=&#034;http://www.iamresearcher.com/&#034; rel=&#034;nofollow&#034; class=&#034;description-link&#034;&gt;http://www.iamresearcher.com/&lt;/a&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/network"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/portal"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/research"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/researcher"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/social"/></rdf:Bag></taxo:topics></item><item rdf:about="http://mkweb.bcgsc.ca/linnet/"><title>Hive Plots - Linear Layout for Network Visualization - Visually Interpreting Network Structure and Content Made Possible</title><description></description><link>http://mkweb.bcgsc.ca/linnet/</link><dc:creator>hotho</dc:creator><dc:date>2011-04-28T21:41:38+02:00</dc:date><dc:subject>network plots visualization </dc:subject><content:encoded>&lt;a itemprop=&#034;url&#034; data-versiondate=&#034;2011-04-28T21:41:38+02:00&#034; href=&#034;http://mkweb.bcgsc.ca/linnet/&#034; rel=&#034;nofollow&#034; class=&#034;description-link&#034;&gt;http://mkweb.bcgsc.ca/linnet/&lt;/a&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/network"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/plots"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/visualization"/></rdf:Bag></taxo:topics></item><item rdf:about="http://an.kaist.ac.kr/traces/WWW2010.html"><title>What is Twitter, a Social Network or a News Media? - WWW&#039;10</title><description></description><link>http://an.kaist.ac.kr/traces/WWW2010.html</link><dc:creator>hotho</dc:creator><dc:date>2011-03-24T10:18:26+01:00</dc:date><dc:subject>dataset network social twitter </dc:subject><content:encoded>&lt;a itemprop=&#034;url&#034; data-versiondate=&#034;2011-03-24T10:18:26+01:00&#034; href=&#034;http://an.kaist.ac.kr/traces/WWW2010.html&#034; rel=&#034;nofollow&#034; 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data-versiondate=&#034;2010-12-05T19:59:23+01:00&#034; href=&#034;http://snap.stanford.edu/data/twitter7.html&#034; rel=&#034;nofollow&#034; class=&#034;description-link&#034;&gt;http://snap.stanford.edu/data/twitter7.html&lt;/a&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/dataset"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/network"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/twitter"/></rdf:Bag></taxo:topics></item><item rdf:about="http://toreopsahl.com/2009/11/10/online-social-network-dataset-now-available/"><title>Online Social Network-dataset now available « Tore Opsahl</title><description></description><link>http://toreopsahl.com/2009/11/10/online-social-network-dataset-now-available/</link><dc:creator>hotho</dc:creator><dc:date>2010-04-30T15:43:34+02:00</dc:date><dc:subject>dataset network social </dc:subject><content:encoded>&lt;a itemprop=&#034;url&#034; data-versiondate=&#034;2010-04-30T15:43:34+02:00&#034; href=&#034;http://toreopsahl.com/2009/11/10/online-social-network-dataset-now-available/&#034; rel=&#034;nofollow&#034; class=&#034;description-link&#034;&gt;http://toreopsahl.com/2009/11/10/online-social-network-dataset-now-available/&lt;/a&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/dataset"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/network"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/social"/></rdf:Bag></taxo:topics></item><item rdf:about="http://snap.stanford.edu/"><title>SNAP: Stanford Network Analysis Platform</title><description></description><link>http://snap.stanford.edu/</link><dc:creator>hotho</dc:creator><dc:date>2010-04-29T16:44:14+02:00</dc:date><dc:subject>analysis dataset network snap software stanford tools </dc:subject><content:encoded>&lt;a itemprop=&#034;url&#034; data-versiondate=&#034;2010-04-29T16:44:14+02:00&#034; href=&#034;http://snap.stanford.edu/&#034; rel=&#034;nofollow&#034; class=&#034;description-link&#034;&gt;http://snap.stanford.edu/&lt;/a&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/analysis"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/dataset"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/network"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/snap"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/software"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/stanford"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/tools"/></rdf:Bag></taxo:topics></item><item rdf:about="http://www-personal.umich.edu/~mejn/netdata/"><title>Network data</title><description></description><link>http://www-personal.umich.edu/~mejn/netdata/</link><dc:creator>hotho</dc:creator><dc:date>2009-11-05T08:54:11+01:00</dc:date><dc:subject>data network research dataset </dc:subject><content:encoded>&lt;a itemprop=&#034;url&#034; data-versiondate=&#034;2009-11-05T08:54:11+01:00&#034; href=&#034;http://www-personal.umich.edu/~mejn/netdata/&#034; rel=&#034;nofollow&#034; class=&#034;description-link&#034;&gt;http://www-personal.umich.edu/~mejn/netdata/&lt;/a&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/data"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/network"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/research"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/dataset"/></rdf:Bag></taxo:topics></item><item rdf:about="http://socialmedia.typepad.com/blog/2008/10/social-network-visualization-eyecandy.html"><title>Social Media Research Blog: Social Network Visualization Eyecandy</title><description>Visualization of graph data is incredibly challenging, particularly when it comes to extremely large, scale-free graphs and social networks. A few simple searches on the Web and you will find some mesmerizing and very cool images. Perhaps the most cited...</description><link>http://socialmedia.typepad.com/blog/2008/10/social-network-visualization-eyecandy.html</link><dc:creator>hotho</dc:creator><dc:date>2009-04-28T15:06:41+02:00</dc:date><dc:subject>blog community detection graph media network post social visualization </dc:subject><content:encoded>&lt;span itemprop=&#034;description&#034;&gt;Visualization of graph data is incredibly challenging, particularly when it comes to extremely large, scale-free graphs and social networks. A few simple searches on the Web and you will find some mesmerizing and very cool images. 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