Knowledge Graph Convolutional Networks

####
Knowledge Graph Convolutional Networks
As humans we use our knowledge, our reasoning and our understanding of situational context to make accurate predictions about the world around us; machine learning doesn’t typically make use of any of this rich information.

The ability to leverage highly interrelated data will yield a step-change in the quality and complexity of predictions that can be made for the same volume of data.

We present Knowledge Graph Convolutional Networks: a method for performing machine learning over a Grakn Knowledge Graph, which captures micro-context and macro-context for any Concept within the graph.

This methodology demonstrates how we can usably combine knowledge, learning and reasoning to build systems that start to look truly intelligent.

Read more about KGCN: https://blog.grakn.ai/knowledge-graph-convolutional-networks-machine-learning-over-reasoned-knowledge-9eb5ce5e0f68

####
James Fletcher,
MEng in Engineering Science from University of Oxford,
Principal Scientist @Grakn Labs
James is the Principal Scientist at Grakn, primarily working on educating the world on how to use a knowledge graph such as Grakn to build cognitive/intelligent systems. For this he is implementing examples as templates and ideas for how clients and community members can innovative in their own specific projects.
With a background in Computer Vision, having co-founded his own startup in veterinary diagnostics, James's priority is to research the new kinds of intelligent system that are enabled by using Grakn as a knowledge graph

There will be pizza, code, and most a certainly a good time!

Timings: 18.30 - 19.00: Networking & Pizza

19.00 - 19.45: Knowledge Graph Convolutional Networks & Introducing Grakn

19.45 - 21.00: Networking & Drinks

Venue:
Royal Academy of Engineering
3 Carlton House Terrace, St.James's, SW1Y 5DG
Please enter the Academy and ask for the ERA Foundation room for the pre-event networking. The talk will happen in the Qasimi north room.