graph – Page 4 – Andrew Fairless, Ph.D.

What I Read: Symbolic Models from Deep Learning

By Andrew Fairless on January 4, 2021December 22, 2020

https://astroautomata.com/paper/symbolic-neural-nets/ Discovering Symbolic Models from Deep Learning with Inductive BiasesPaper Code Interactive NotebookPaper authors: Miles Cranmer, Alvaro Sanchez-Gonzalez, Peter Battaglia, Rui Xu, Kyle Cranmer, David Spergel, Shirley Ho “…when doesContinue readingWhat I Read: Symbolic Models from Deep Learning

What I Read: Differentiable Reasoning over Text

By Andrew Fairless on January 1, 2021December 22, 2020

https://blog.ml.cmu.edu/2020/05/15/differentiable-reasoning-over-text/ Differentiable Reasoning over TextAuthorsBhuwan DhingraPublishedMay 15, 2020 “Modern search engines not only retrieve a list of pages relevant to a query but often try to directly answer our questionsContinue readingWhat I Read: Differentiable Reasoning over Text

What I Read: Learning Neural Causal Models

By Andrew Fairless on December 30, 2020December 20, 2020

https://arxiv.org/abs/1910.01075Learning Neural Causal Models from Unknown InterventionsNan Rosemary Ke, Olexa Bilaniuk, Anirudh Goyal, Stefan Bauer, Hugo Larochelle, Chris Pal, Yoshua Bengio “We present a new framework for meta-learning causal modelsContinue readingWhat I Read: Learning Neural Causal Models

What I Read: Guide to Graph Neural Networks

By Andrew Fairless on December 20, 2020December 8, 2020

https://medium.com/dair-ai/an-illustrated-guide-to-graph-neural-networks-d5564a551783 An Illustrated Guide to Graph Neural NetworksA breakdown of the inner workings of GNNs…Rishabh AnandMar 30 “Here, I’ll cover the basics of a simple Graph Neural Network (GNN) andContinue readingWhat I Read: Guide to Graph Neural Networks

What I Read: Transformers Graph Neural Networks

By Andrew Fairless on December 17, 2020December 4, 2020

https://graphdeeplearning.github.io/post/transformers-are-gnns/ Transformers are Graph Neural NetworksChaitanya JoshiFeb 12, 2020 “Through this post, I want to establish links between Graph Neural Networks (GNNs) and Transformers. I’ll talk about the intuitions behindContinue readingWhat I Read: Transformers Graph Neural Networks

What I Read: Neural State Machine

By Andrew Fairless on December 16, 2020December 4, 2020

https://arxiv.org/abs/1907.03950 Learning by Abstraction: The Neural State MachineDrew A. Hudson, Christopher D. Manning “We introduce the Neural State Machine, seeking to bridge the gap between the neural and symbolic viewsContinue readingWhat I Read: Neural State Machine

What I Read: scalable graph machine learning

By Andrew Fairless on December 3, 2020November 28, 2020

https://www.kdnuggets.com/2019/12/scalable-graph-machine-learning.html Scalable graph machine learning: a mountain we can climb?By Kevin Jung, Software Engineer at CSIRO Data61 “In this article, we will take a closer look at scalability for graphContinue readingWhat I Read: scalable graph machine learning

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