Keynote Speakers
GraphNews
Michael Bronstein on LinkedIn: #cancer #gnns #deeplearning
benedekrozemberczki/datasets
A repository of pretty cool datasets that I collected for network science and machine learning research. - benedekrozemberczki/datasets
Michael Bronstein on LinkedIn: Predictions and hopes for Graph ML in 2021
A beautiful compilation of the exciting research that happened in the world of Graph ML as well as the predictions of where the field is heading to according...
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Emil Eifrem on LinkedIn: Introduction and Demo Graph Drawing with Arrows.app
I would rate this app as the most useful app since MS Excel :) Regardless of if you are familiar with Neo4j or not......
Graph Neural Networks for Multi-Relational Data
From GCNs to R-GCNs: encoding the structure of Knowledge Graphs with neural architectures (examples in NumPy code)
MIT Machine Learning Uses ‘Graph Grammar’ to Automate and Optimize Robot Design
Geometric ML becomes real in fundamental sciences | by Michael Bronstein | Dec, 2020 | Towards Data Science
From protein folding to new antibiotics, Graph ML methods shine in biochemistry and drug design applications.
SimGNN
Similarity Computation via Graph Neural Networks
A Practical Guide to Build an Enterprise Knowledge Graph for Investment Analysis
How to solve the practical problems when building a real Enterprise Knowledge Graph service
Xavier Bresson on LinkedIn: My main talks on Graph Neural Networks in 2020 1. Introduction to
My main talks on Graph Neural Networks in 2020 1. Introduction to GNNs https://lnkd.in/gF_NZ-5 Slides: https://rb.gy/yabvud 2. Recent developments in...
Michael Bronstein on LinkedIn: #gnns #polypharmacy #drugs
I'm in love with GNNs. Yet another amazing application in computational biology. How about detecting poly-pharmacy (using multiple drugs at the same time...
Aleksa Gordić on LinkedIn: PinSage: A new graph convolutional neural network for web-scale recommender
A beautiful example of how GNNs (graph neural networks) can be leveraged in massive-scale (billions of nodes!) production systems - such as the recommender...
Michael Bronstein on LinkedIn: #TrustworthyAI #KnowledgeRepresentation #Reasoning
Graph Neural Networks Meet Neural-Symbolic Computing: A Survey and Perspective Lamb et al.: https://lnkd.in/dE3ZkMF #TrustworthyAI #KnowledgeRepresentation...
Knowledge Graphs!
Semantic Linked Knowledge Web Data Graphs?
Enterprise Knowledge Graph Trends for 2021
This is my third annual post on Enterprise Knowledge Graph (EKG) trends. You can also find my 2019 and 2020 posts on this blog, and I…
Michael Bronstein on LinkedIn: Graph Convolutional Networks (GCN) | GNN Paper Explained
The final video for this year - Graph Convolutional Networks (GCNs)! The most cited paper in the GNN literature. As promised I'm continuing to work on...
Giuseppe Futia, PhD on LinkedIn: #machinelearning #graphs #datascience
AutoGL an Auto-ML Framework & Toolkit for Machine Learning on Graph AutoGL (Auto Graph Learning) is able to automatically handle all stages of graph learning...
Google’s REALM — A Knowledge-base Augmented Language Model
Google has published a new way of pre-training a language model which is augmented using a knowledge retrieval mechanism, that looks up…
Geometric ML becomes real in fundamental sciences
From protein folding to new antibiotics, Graph ML methods shine in biochemistry and drug design applications.
New Protégé Pizza Tutorial
New Pizza Tutorial for Protege 5. Includes basic ontology development plus new sections for SWRL, SPARQL, and SHACL.
Aleksa Gordić on LinkedIn: Graph Attention Networks (GATs) | GNN Paper Explained
Graph neural networks, and geometric deep learning in general, are getting ever more important and we've seen trends on big conferences that back up that...
How do users interact with a Knowledge Graph?
The purpose of a knowledge graph is to answer a user's questions. Some of the questions may be known upfront, while some questions users may never think of themselves.
PageRank algorithm, fully explained
Today’s post is about Google algorithm, commonly defined as the PageRank algorithm.
A Friendly Introduction to Graph Neural Networks
Despite being what can be a confusing topic, graph neural networks can be distilled into just a handful of simple concepts. Read on to find out more.
Boxes and Stars - Modelling Relationships in RDF Graphs
Modelling complex relationships in RDF graphs
Top 5 SEO Trends 2021 that you should know!
Top 5 SEO predictions for 2021: it's time to re-think your content marketing strategy while focusing on continuous innovation and AI.
Ryan Wisnesky on LinkedIn: Hi all, I have developed new algorithms for managing semantics (i.e
Hi all, I have developed new algorithms for managing semantics (i.e. logical assertions) in knowledge graphs - faster algorithms for automated deduction...