InTDS ArchivebyMichael Galkin·Jun 18, 2024Foundation Models in Graph & Geometric Deep LearningIn this post, we argue that the era of Graph FMs has already begun and provide a few examples of how one can use them already today.A response icon8A response icon8
InTDS ArchivebyMichael Galkin·Jan 16, 2024Graph & Geometric ML in 2024: Where We Are and What’s Next (Part II — Applications)Trends and recent advancements in Graph and Geometric Deep LearningA response icon5A response icon5
InTDS ArchivebyMichael Galkin·Jan 16, 2024Graph & Geometric ML in 2024: Where We Are and What’s Next (Part I — Theory & Architectures)Trends and recent advancements in Graph and Geometric Deep LearningA response icon1A response icon1
InTDS ArchivebyMichael Galkin·Nov 3, 2023ULTRA: Foundation Models for Knowledge Graph ReasoningOne model to rule them allA response icon4A response icon4
InTDS ArchivebyMichael Galkin·Aug 6, 2023Graph Machine Learning @ ICML 2023Recent advancements and hot trends, August 2023 editionA response icon5A response icon5
InTDS ArchivebyMichael Galkin·Mar 28, 2023Neural Graph DatabasesA new milestone in graph data managementA response icon3A response icon3
InTDS ArchivebyMichael Galkin·Jan 1, 2023Graph ML in 2023: The State of AffairsHot trends and major advancementsA response icon3A response icon3
InTDS ArchivebyMichael Galkin·Nov 26, 2022Denoising Diffusion Generative Models in Graph MLIs Denoising Diffusion all you need?
InTDS ArchivebyMichael Galkin·Jul 25, 2022Graph Machine Learning @ ICML 2022Recent advancements and hot trends, July 2022 editionA response icon4A response icon4
InTDS ArchivebyMichael Galkin·Jun 14, 2022GraphGPS: Navigating Graph TransformersRecipes for cooking the best graph transformersA response icon4A response icon4
