hocine cherifi@HocineCherifi
⏳ 1 week left to submit to COMPLEX NETWORKS 2026!
📅 Deadline: Sept 2, 2026
📍 Granada, Spain | Dec 2–4
📄 Full papers & extended abstracts welcome
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#ComplexNetworks #NetworkScience #GraphLearning
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Posts with #Graphlearning
#Graphlearning
Public posts on X that use #Graphlearning.
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Feng Xia@fxia61This paper was published earlier 2026 in ACM TOIS! We're delighted that it has been selected for presentation at #SIGIR2026 in Melbourne. We'd love to see you there! DOI (open access): #graphlearning #llm #token #largelanguagemodel #graph #AI #research
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Data Science Demystified@datascintst999#234 Graph Learning Explained: How Machines Understand Complex Relationships #GraphLearning #MachineLearning #GraphNeuralNetworks #DataScience #ArtificialIntelligence #DeepLearning #GraphTheory #AI #DataScienceDemystifiedDailyDose05535
Kumo@Kumo_ai_teamUse #GraphLearning on your enterprise data to improve and test the #CustomerSegmentation that drives your growth strategies002109- hocine cherifi@HocineCherifi⏳ Deadline extended for COMPLEX NETWORKS 2026! Final deadline: Sept 13, 2026 📄 Full papers & extended abstracts welcome 📍 Granada, Spain | Dec 2–4 🔗 #ComplexNetworks #NetworkScience #GraphLearning
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Michael Bronstein@mmbronsteinOur work at Twitter with @emaros96 @b_p_chamberlain @ffabffrasca @aittalam @frederickmonti introducing Temporal Graph Networks: new GNN architecture for continuous-time dynamic graphs. #geometricdeeplearning #GNN #graphlearning127103
IEEE Signal Processing Society@IEEEsps📢 Deadline Extended! Submit your manuscript for the IEEE TSIPN Special Issue on Learning on Graphs for Biology & Medicine by Nov 1, 2024. Don’t miss your chance to contribute to cutting-edge research! 🧬📊 #IEEE #GraphLearning #Biomedicine #Research
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📢 Postdoc Opportunity: Graph Learning at the Max Planck Institute of Biochemistry, Germany. Develop next-generation graph machine learning algorithms. Apply by 30 Sept 2026. #Postdoc #GraphLearning #MachineLearning #AI #Germany #Maxplanck002228- Kumo@Kumo_ai_team#GraphLearning is an amazing technology that can monitor the health of your “steps” for signs of joint injuries, muscular dystrophy and even strokes #PyG #PyTorchGeometric #GraphNeuralNetworks005436
Jundong Li@LiJundongCheck out our recently released PyGDebias package that integrates the SOTA fairness and bias mitigation algorithms in graph machine learning, along with the benchmark datasets. #graphlearning #fairness #biasYushun Dong @Yushun_Dong🚀 Introducing PyGDebias v0.1.1, an open-source library dedicated to fairness in graph mining algorithms! PyGDebias comes packed with 26 graph datasets, making it a diverse and comprehensive toolkit for fairness research on graphs.02212.3K
Yushun Dong@Yushun_Dong🚀 Introducing PyGDebias v0.1.1, an open-source library dedicated to fairness in graph mining algorithms! PyGDebias comes packed with 26 graph datasets, making it a diverse and comprehensive toolkit for fairness research on graphs.
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sirolf@sirolfgMachine learning and database theory combine well: A Neuro-Symbolic Framework for Answering Graph Pattern Queries in Knowledge Graphs Read more: #nesy #graphlearning #knowledgegraph028396- Kumo@Kumo_ai_team#GraphLearning is a powerful tool for #personalization. #GraphNeuralNetworks improve the performance and structure of recommender systems. Learn more005282
Join us for the Stanford Graph Learning Workshop 2025! 🗓️Oct 14, 2025 📍Stanford University 🧠Topics: Agents, RFMs & LLM Inference. Save your spot to explore the future of #AI, #LLMs and #GraphLearning with leading experts. Register now:
34229217.7K- Kumo@Kumo_ai_team📊#GNN case study: 73% better predicting “next best" offers at an online bank in 3-days of modeling across 3B records. Learn more: #PredictiveAI #GraphLearning #GraphNeuralNetworks
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💻 New Cyber Daily Report Blog Post! Title: Enhancing Lateral Movement Detection with Graph Learning Author: Mahdi Rabbani Editor: Windhya Rankothge Link: #GraphLearning #MachineLearning #LateralMovementDetection #AdvancedPersistentThreat02271
Daniele Malitesta@dmalitestaPre-print and code for our #RecSys2024 @ACMRecSys paper are now out! Check them out 🚀🚀 * Pre-print: * Code: Don't forget to save the date of our presentation: 📅 October 16, 2024 (#GraphLearning sessionDaniele Malitesta @dmalitestaI’m happy to share “A Novel Evaluation Perspective on #GNNs-based Recommender Systems through the Topology of the User-Item Graph” has been accepted to the #reproducibility track of #RecSys2024 @ACMRecSys! w/ @scne @alberto_mancino @walteranelli @TommasoDiNoia @DiSciascioEugen1515737- Daniele Malitesta@dmalitestaI’m happy to share “A Novel Evaluation Perspective on #GNNs-based Recommender Systems through the Topology of the User-Item Graph” has been accepted to the #reproducibility track of #RecSys2024 @ACMRecSys! w/ @scne @alberto_mancino @walteranelli @TommasoDiNoia @DiSciascioEugen22222.1K
The1 Replied@agent_the1🚀 Exciting news! The1's latest research provides a benchmark for graph learning datasets, including applications in NLP and computer vision 📊🔍 Stay ahead of the curve with #The1! #GraphLearning #NLP #ComputerVision00034- Kumo@Kumo_ai_teamDiscover how to overcome the challenges of scaling #graphlearning using a #microservices approach in our upcoming webinar
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Johannes C. Paetzold@jocpaeBeyond excited to share our preprint VesselGraph on Whole Brain Vessel Graphs: A Dataset and Benchmark for Graph Learning and Neuroscience in collaboration with @erturklab @guennemann @DQBM_uzh @UZH_en @TU_Muenchen link: git:
1070267- Johannes C. Paetzold@jocpae@jocpae(2/n) We extract a set of standardized whole-brain vessel graphs based on whole, segmented mouse brains from various imaging sources & publicly release our data in an easily accessible and adaptable format for #graphlearning by implementing #OGB and #PyTorchGeometric data loaders
118 - Kumo@Kumo_ai_team#GraphLearning is a powerful tool for personalization. #GraphNeuralNetworks improve the performance of recommender systems in customer use case. Learn more #CLV #CustomerRetention226649
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