Reader small image

You're reading from  Hands-On Mathematics for Deep Learning

Product typeBook
Published inJun 2020
Reading LevelIntermediate
PublisherPackt
ISBN-139781838647292
Edition1st Edition
Languages
Right arrow
Author (1)
Jay Dawani
Jay Dawani
author image
Jay Dawani

Jay Dawani is a former professional swimmer turned mathematician and computer scientist. He is also a Forbes 30 Under 30 Fellow. At present, he is the Director of Artificial Intelligence at Geometric Energy Corporation (NATO CAGE) and the CEO of Lemurian Labs - a startup he founded that is developing the next generation of autonomy, intelligent process automation, and driver intelligence. Previously he has also been the technology and R&D advisor to Spacebit Capital. He has spent the last three years researching at the frontiers of AI with a focus on reinforcement learning, open-ended learning, deep learning, quantum machine learning, human-machine interaction, multi-agent and complex systems, and artificial general intelligence.
Read more about Jay Dawani

Right arrow

Graph Laplacian

Earlier in this chapter, in the Adjacency matrix section, we learned about the adjacency matrix and how we can use it to tell what the structure of a graph is. However, there are other ways of representing graphs in matrix form.

Now, let's suppose we have an undirected, unweighted graph. Then, its Laplacian matrix will be a symmetric n × n matrix, L, whose elements are as follows:

Here, . We can also write this as follows:

Here, Ai,j is the adjacency matrix and δi,j is the Kronecker delta. We can rewrite this in matrix form, as follows:

Here, we have the following:

Similarly, we can also write the graph Laplacian matrix for a weighted graph by replacing the adjacency matrix here with the one we defined previously for weighted graphs.

lock icon
The rest of the page is locked
Previous PageNext Page
You have been reading a chapter from
Hands-On Mathematics for Deep Learning
Published in: Jun 2020Publisher: PacktISBN-13: 9781838647292

Author (1)

author image
Jay Dawani

Jay Dawani is a former professional swimmer turned mathematician and computer scientist. He is also a Forbes 30 Under 30 Fellow. At present, he is the Director of Artificial Intelligence at Geometric Energy Corporation (NATO CAGE) and the CEO of Lemurian Labs - a startup he founded that is developing the next generation of autonomy, intelligent process automation, and driver intelligence. Previously he has also been the technology and R&D advisor to Spacebit Capital. He has spent the last three years researching at the frontiers of AI with a focus on reinforcement learning, open-ended learning, deep learning, quantum machine learning, human-machine interaction, multi-agent and complex systems, and artificial general intelligence.
Read more about Jay Dawani