Michael GalkininTowards Data ScienceFoundation 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.20 min read·5 days ago--6--6

Michael GalkininTowards Data ScienceGraph & Geometric ML in 2024: Where We Are and What’s Next (Part II — Applications)Trends and recent advancements in Graph and Geometric Deep Learning42 min read·Jan 16, 2024--5--5

Michael GalkininTowards Data ScienceGraph & Geometric ML in 2024: Where We Are and What’s Next (Part I — Theory & Architectures)Trends and recent advancements in Graph and Geometric Deep Learning30 min read·Jan 16, 2024--2--2

Michael GalkininTowards Data ScienceULTRA: Foundation Models for Knowledge Graph ReasoningOne model to rule them all10 min read·Nov 3, 2023--5--5

Michael GalkininTowards Data ScienceGraph Machine Learning @ ICML 2023Recent advancements and hot trends, August 2023 edition16 min read·Aug 6, 2023--5--5

Michael GalkininTowards Data ScienceNeural Graph DatabasesA new milestone in graph data management14 min read·Mar 28, 2023--3--3

Michael GalkininTowards Data ScienceGraph ML in 2023: The State of AffairsHot trends and major advancements26 min read·Jan 1, 2023--3--3

Michael GalkininTowards Data ScienceDenoising Diffusion Generative Models in Graph MLIs Denoising Diffusion all you need?8 min read·Nov 26, 2022----

Michael GalkininTowards Data ScienceGraph Machine Learning @ ICML 2022Recent advancements and hot trends, July 2022 edition29 min read·Jul 25, 2022--4--4

Michael GalkininTowards Data ScienceGraphGPS: Navigating Graph TransformersRecipes for cooking the best graph transformers12 min read·Jun 14, 2022--4--4