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DSC Weekly Digest 04 Jan 2022: Can Machine Learning Do Symbolic Manipulation? - DataScienceCentral.com
DSC Weekly Digest 04 Jan 2022: Can Machine Learning Do Symbolic Manipulation? - DataScienceCentral.com
Can Machine Learning Do Symbolic Manipulation?  I spent some time over the holidays engaged in a fascinating online conversation. The gist of it was a variation of an argument that has been going on in the realm of artificial intelligence from the time of Minsky and Seymour Papert: Whether it is possible for neural networks to… Read More »DSC Weekly Digest 04 Jan 2022: Can Machine Learning Do Symbolic Manipulation?
·datasciencecentral.com·
DSC Weekly Digest 04 Jan 2022: Can Machine Learning Do Symbolic Manipulation? - DataScienceCentral.com
What is Graph Intelligence? - Gradient Flow
What is Graph Intelligence? - Gradient Flow
How and why the best companies are adopting Graph Visual Analytics, Graph AI, and Graph Neural Networks. By Leo Meyerovich and Ben Lorica. [A version of this post originally appeared on the Graphistry blog.] In this post, we highlight the current state of Graph Intelligence, a new technology category around new tools and techniques forContinue reading "What is Graph Intelligence?"
·gradientflow.com·
What is Graph Intelligence? - Gradient Flow
Where Semantics and Machine Learning Converge - DataScienceCentral.com
Where Semantics and Machine Learning Converge - DataScienceCentral.com
Artificial Intelligence has a long history of oscillating between two somewhat contradictory poles. On one side, exemplified by Noam Chomsky, Marvin Minsky, Seymour Papert, and many others, is the idea that cognitive intelligence was algorithmic in nature – that there were a set of fundamental precepts that formed the foundation of language, and by extension,… Read More »Where Semantics and Machine Learning Converge
·datasciencecentral.com·
Where Semantics and Machine Learning Converge - DataScienceCentral.com
Deep Learning with Graph-Structured Representations
Deep Learning with Graph-Structured Representations
Very honored to receive the ELLIS PhD Award for my thesis on Deep Learning with Graph-Structured Representations -- alongside with with @NagraniArsha for her work on multimodal DL (congrats!) https://t.co/FUzNA87okN pic.twitter.com/W2KrbQN7yS— Thomas Kipf (@thomaskipf) December 9, 2021
·twitter.com·
Deep Learning with Graph-Structured Representations
Using subgraphs for more expressive GNNs
Using subgraphs for more expressive GNNs
The expressive power of Message-Passing Graph Neural Networks is inherently limited due to their equivalence to the Weisfeiler-Lehman graph isomorphism...
·linkedin.com·
Using subgraphs for more expressive GNNs
The Open Application Group (OAGi) and the Industrial Ontologies Foundry (IOF) have signed an agreement to produce industrial ontologies
The Open Application Group (OAGi) and the Industrial Ontologies Foundry (IOF) have signed an agreement to produce industrial ontologies
"The Open Application Group (OAGi) and the Industrial Ontologies Foundry (IOF) have signed an agreement to produce industrial ontologies." [PR] https://t.co/zz511UBuYE— Aaron Bradley (@aaranged) March 3, 2021
·twitter.com·
The Open Application Group (OAGi) and the Industrial Ontologies Foundry (IOF) have signed an agreement to produce industrial ontologies
Building (up) GraphNNs!
Building (up) GraphNNs!
Sometime I become so addicted to a particular framework that I completely forget about how the world is changing out there. Therefore…
·medium.com·
Building (up) GraphNNs!
SpikeX: spaCy Pipes for Knowledge Extraction
SpikeX: spaCy Pipes for Knowledge Extraction
SpikeX: spaCy Pipes for Knowledge Extraction 🧶 WikiPageX links Wikipedia pages to chunks in text 💎 ClusterX picks noun chunks in a text and clusters... 13 comments on LinkedIn
·linkedin.com·
SpikeX: spaCy Pipes for Knowledge Extraction
A new class of GNNs grand + blend
A new class of GNNs grand + blend
A new class of GNNs! This Tuesday in the #graph reading group, James Rowbottom and Ben Chamberlain present their "GRAND: Graph Neural Diffusion" paper ...
·linkedin.com·
A new class of GNNs grand + blend
Thomas Kipf on Twitter
Thomas Kipf on Twitter
To showcase best practices for building/training Graph Neural Nets in JAX, we put together a comprehensive example for molecular activity prediction using Flax & JraphOfficial Flax GNN example: https://t.co/vrsyYpcdhhGreat work by @BigAmeya w/ collaborators @ Brain & DeepMind https://t.co/8L0UKgQxj5 pic.twitter.com/Jzzvxt7a3F— Thomas Kipf (@thomaskipf) October 8, 2021
·twitter.com·
Thomas Kipf on Twitter
What are graph neural networks (GNN)?
What are graph neural networks (GNN)?
Graph neural networks (GNN) are a type of machine learning algorithm that can extract important information from graphs and make useful predictions.
·bdtechtalks.com·
What are graph neural networks (GNN)?
Ivo Velitchkov on Twitter
Ivo Velitchkov on Twitter
Here's the recording of my session "Better Project Management with Knowledge Graphs" at the PMI Fair Benelux 2021.#projectmanagement #knowledgegraph #PKGhttps://t.co/ldG671YDpr— Ivo Velitchkov (@kvistgaard) October 18, 2021
·twitter.com·
Ivo Velitchkov on Twitter
Introducing WebQA : A Multi-hop, Multi-modal & Open Domain Reasoning Challenge & Benchmark
Introducing WebQA : A Multi-hop, Multi-modal & Open Domain Reasoning Challenge & Benchmark
We are proud to introduce WebQA, a dataset for multi-hop, multi-modal open-domain question answering challenge, to be hosted at NeurIPS 2021 Competition Track. Designed to simulate the heterogeneous information landscape one might expect when performing web search, WebQA contains 46K knowledge-seeking queries whose answers are to be found in either images or text snippets, where a system must…
·blogs.bing.com·
Introducing WebQA : A Multi-hop, Multi-modal & Open Domain Reasoning Challenge & Benchmark