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Aaron Bradley on Twitter
Aaron Bradley on Twitter
Anti-Money Laundering Alert Optimization Using Machine Learning with Graphs https://t.co/e7fQg57Mrt pic.twitter.com/8nZ7QzeUD5— Aaron Bradley (@aaranged) December 15, 2021
·twitter.com·
Aaron Bradley on Twitter
Aaron Bradley on Twitter
Aaron Bradley on Twitter
ISEEQ: Information Seeking Question Generation using Dynamic Meta-Information Retrieval and Knowledge Graphs @manasgaur90 et al. https://t.co/Gg6s7J0kwH pic.twitter.com/kNbaji06Vf— Aaron Bradley (@aaranged) December 15, 2021
·twitter.com·
Aaron Bradley on Twitter
Aaron Bradley on Twitter
Aaron Bradley on Twitter
A Simple Standard for Sharing Ontological Mappings (SSSOM) @NicoMatentzoglu + ~40 others https://t.co/rCAyGakxdY pic.twitter.com/GK0fzPFx6q— Aaron Bradley (@aaranged) December 15, 2021
·twitter.com·
Aaron Bradley on Twitter
Michael Bronstein on Twitter
Michael Bronstein on Twitter
What if we model a graph as a set of subgraphs instead of a set of interconnected nodes? Hint: expressive power + equivariance! 🧵Joint work by a super team: @beabevi_ * @dereklim_lzh * @balasrini32 @ChenCaiUCSD @gblearning42 @mmbronstein @HaggaiMaronhttps://t.co/6rW4e47RhN pic.twitter.com/Ajl8L5xdDc— Fabrizio Frasca (@ffabffrasca) December 15, 2021
·twitter.com·
Michael Bronstein on Twitter
Aaron Bradley on Twitter
Aaron Bradley on Twitter
MedGraph: An experimental semantic information retrieval method using knowledge graph embedding for the biomedical citations indexed in PubMed https://t.co/B3tmoVilDt pic.twitter.com/DvEVoU53ec— Aaron Bradley (@aaranged) December 14, 2021
·twitter.com·
Aaron Bradley on Twitter
Aaron Bradley on Twitter
Aaron Bradley on Twitter
Graph-based hierarchical record clustering for unsupervised entity resolution https://t.co/I0saMXcQFL pic.twitter.com/eB7Cphflp3— Aaron Bradley (@aaranged) December 14, 2021
·twitter.com·
Aaron Bradley on Twitter
Learning SPARQL on Twitter
Learning SPARQL on Twitter
Use our SPARQL micro-services to query #PubMedCentral with #SPARQL using a PMID or PMCID, and get article metadata in #RDF.https://t.co/1RKvb9GZkvhttps://t.co/XxjTUy2Gut@pubmed @wimmics @Inria @uca_research @Laboratoire_I3S #ScientificLitterature pic.twitter.com/bm8OdpzoaN— Michel Franck (@franck_michel2) December 7, 2021
·twitter.com·
Learning SPARQL on Twitter
Aaron Bradley on Twitter
Aaron Bradley on Twitter
Embedding knowledge on ontology into the corpus by topic to improve the performance of deep learning methods in sentiment analysis - Scientific Reports https://t.co/W0lKPRCh84 #DL #AI #ML #DeepLearning #ArtificialIntelligence #MachineLearning #ComputerVision #AutonomousVehicles— Deep_In_Depth (@Deep_In_Depth) December 11, 2021
·twitter.com·
Aaron Bradley on Twitter
Aaron Bradley on Twitter
Aaron Bradley on Twitter
UFO: Unified Foundational Ontology / Giancarlo Guizzardi et al. https://t.co/GuTFxstIqV pic.twitter.com/9BJG1GUdIt— Aaron Bradley (@aaranged) December 16, 2021
·twitter.com·
Aaron Bradley on Twitter
How Data Modeling is different today
How Data Modeling is different today
Over the last 20 years my life revolved around doing “everything modeling” - building models, discussing modeling, teaching modeling and so on. Unsurprisingly, I have an opinion about models and modeling.
·linkedin.com·
How Data Modeling is different today
Reflections of knowledge
Reflections of knowledge
Designing Web APIs for sustainable interactions within decentralized knowledge graph ecosystems ◆ Web services emerged in the late 1990s as a way to access specific pieces of remote functionality, building on the standards-driven stability brought by the universal protocol that HTTP was readily becoming. Interestingly, the Web itself has drastically changed since…
·ruben.verborgh.org·
Reflections of knowledge
Using subgraphs for more expressive GNNs
Using subgraphs for more expressive GNNs
The expressive power of Message-Passing Graph Neural Networks is inherently limited due to their equivalence to the Weisfeiler-Lehman graph isomorphism...
·linkedin.com·
Using subgraphs for more expressive GNNs