Open in app

Sign In

Write

Sign In

Michael Galkin
Michael Galkin

2.7K Followers

Home

About

Published in

Towards Data Science

·Aug 6

Graph Machine Learning @ ICML 2023

Recent advancements and hot trends, August 2023 edition — Magnificent beaches and tropical Hawaiian landscapes 🌴did not turn brave scientists away from attending the International Conference on Machine Learning in Honolulu and presenting their recent work! Let’s see what’s new in our favorite Graph Machine Learning area. Thanks Santiago Miret for proofreading the post. To make the post less…

Artificial Intelligence

16 min read

Graph Machine Learning @ ICML 2023
Graph Machine Learning @ ICML 2023
Artificial Intelligence

16 min read


Published in

Towards Data Science

·Mar 28

Neural Graph Databases

A new milestone in graph data management — We introduce the concept of Neural Graph Databases as the next step in the evolution of graph databases. Tailored for large incomplete graphs and on-the-fly inference of missing edges using graph representation learning, neural reasoning maintains high expressiveness and supports complex logical queries similar to standard graph query languages. This…

Machine Learning

14 min read

Neural Graph Databases
Neural Graph Databases
Machine Learning

14 min read


Published in

Towards Data Science

·Jan 1

Graph ML in 2023: The State of Affairs

Hot trends and major advancements — 2022 comes to an end and it is about time to sit down and reflect upon the achievements made in Graph ML as well as to hypothesize about possible breakthroughs in 2023. Tune in 🎄☕ The article is written together with Hongyu Ren (Stanford University), Zhaocheng Zhu (Mila & University…

Artificial Intelligence

26 min read

Graph ML in 2023: The State of Affairs
Graph ML in 2023: The State of Affairs
Artificial Intelligence

26 min read


Published in

Towards Data Science

·Nov 26, 2022

Denoising Diffusion Generative Models in Graph ML

Is Denoising Diffusion all you need? — The breakthrough in Denoising Diffusion Probabilistic Models (DDPM) happened about 2 years ago. Since then, we observe dramatic improvements in generation tasks: GLIDE, DALL-E 2, Imagen, Stable Diffusion for images, Diffusion-LM in language modeling, diffusion for video sequences, and even diffusion for reinforcement learning. Diffusion might be the biggest trend…

Machine Learning

8 min read

Denoising Diffusion Generative Models in Graph ML
Denoising Diffusion Generative Models in Graph ML
Machine Learning

8 min read


Published in

Towards Data Science

·Jul 25, 2022

Graph Machine Learning @ ICML 2022

Recent advancements and hot trends, July 2022 edition — International Conference on Machine Learning (ICML) is one of the premier venues where researchers publish their best work. ICML 2022 was packed with hundreds of papers and numerous workshops dedicated to graphs. We share the overview of the hottest research areas 🔥 in Graph ML. This post was written by…

Machine Learning

29 min read

Graph Machine Learning @ ICML 2022
Graph Machine Learning @ ICML 2022
Machine Learning

29 min read


Published in

Towards Data Science

·Jun 14, 2022

GraphGPS: Navigating Graph Transformers

Recipes for cooking the best graph transformers — In 2021, graph transformers (GT) won recent molecular property prediction challenges thanks to alleviating many issues pertaining to vanilla message passing GNNs. Here, we try to organize numerous freshly developed GT models into a single GraphGPS framework to enable general, powerful, and scalable graph transformers with linear complexity for all…

Machine Learning

12 min read

GraphGPS: Navigating Graph Transformers
GraphGPS: Navigating Graph Transformers
Machine Learning

12 min read


Published in

Towards Data Science

·Mar 24, 2022

Inductive Link Prediction in Knowledge Graphs

Starting a new Inductive Link Prediction Challenge 2022 — Since very 2011, the area of representation learning over Knowledge Graphs has been dominated by one task: transductive link prediction. Is it still relevant in 2022? 🤔 Rather not. In the transductive setup (🖼 ☝️) we perform inference (our link prediction) over the same graph seen at training time. We…

Machine Learning

5 min read

Inductive Link Prediction in Knowledge Graphs
Inductive Link Prediction in Knowledge Graphs
Machine Learning

5 min read


Published in

Towards Data Science

·Dec 28, 2021

Graph ML in 2022: Where Are We Now?

Hot trends and major advancements — It’s been quite a year for Graph ML — thousands of papers, numerous conferences and workshops… How do we catch up with so many cool things happening around? Well, we are puzzled as well and decided to present a structured look at Graph ML highlighting 🔥 trends and major advancements. …

Machine Learning

16 min read

Graph ML in 2022: Where Are We Now?
Graph ML in 2022: Where Are We Now?
Machine Learning

16 min read


Nov 15, 2021

Knowledge Graphs @ EMNLP 2021

Your regular digest of KG research, November edition — I didn’t make it to Punta Cana this year 😢 but I’m happy (remotely) for the folks who managed to get there in spite of all traveling restrictions! Premium content inside 🏖 The autumn got very busy and I’d like to try a shorter format: each big topic has one…

Knowledge Graph

9 min read

Knowledge Graphs @ EMNLP 2021
Knowledge Graphs @ EMNLP 2021
Knowledge Graph

9 min read


Published in

Towards Data Science

·Aug 5, 2021

Knowledge Graphs in Natural Language Processing @ ACL 2021

Your guide to the KG-related NLP research, ACL edition — Welcome to the third iteration of our regular overview of NLP papers around Knowledge Graphs, this time published at ACL 2021! What will be (or has been) trending this year that you wouldn’t want to miss? 👀 ACL’21 remains to be one of the largest NLP venues: 700+ full papers…

Knowledge Graph

19 min read

Knowledge Graphs in Natural Language Processing @ ACL 2021
Knowledge Graphs in Natural Language Processing @ ACL 2021
Knowledge Graph

19 min read

Michael Galkin

Michael Galkin

2.7K Followers

AI Research Scientist @ Intel Labs. Working on Graph ML, Geometric DL, and Knowledge Graphs

Following
  • Gadi Singer

    Gadi Singer

  • Michael Bronstein

    Michael Bronstein

  • PyTorch Geometric

    PyTorch Geometric

  • Shenyang(Andy) Huang

    Shenyang(Andy) Huang

  • Charles Tapley Hoyt

    Charles Tapley Hoyt

See all (14)

Help

Status

Writers

Blog

Careers

Privacy

Terms

About

Text to speech

Teams