neural network – Page 26 – Andrew Fairless, Ph.D.

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: Symbolic Mathematics, Neural Networks

By Andrew Fairless on December 27, 2020December 20, 2020

https://www.quantamagazine.org/symbolic-mathematics-finally-yields-to-neural-networks-20200520/ artificial intelligenceSymbolic Mathematics Finally Yields to Neural NetworksAfter translating some of math’s complicated equations, researchers have created an AI system that they hope will answer even bigger questions.by StephenContinue readingWhat I Read: Symbolic Mathematics, Neural Networks

What I Read: Deep Generative Models

By Andrew Fairless on December 25, 2020December 13, 2020

https://medium.com/@jrodthoughts/microsoft-research-unveils-three-efforts-to-advance-deep-generative-models-b1d2fe3395e8 Microsoft Research Unveils Three Efforts to Advance Deep Generative ModelsOptimus, FQ-GAN and Prevalent bring new ideas to apply generative models at large scale.Jesus RodriguezApr 27 “With the emergence ofContinue readingWhat I Read: Deep Generative Models

What I Read: Neural Networks to Find Answers in Tables

By Andrew Fairless on December 24, 2020December 13, 2020

https://ai.googleblog.com/2020/04/using-neural-networks-to-find-answers.html?ref=hvper.com Using Neural Networks to Find Answers in TablesThursday, April 30, 2020Posted by Thomas Müller, Software Engineer, Google Research “Much of the world’s information is stored in the form ofContinue readingWhat I Read: Neural Networks to Find Answers in Tables

What I Read: Common Sense Computers

By Andrew Fairless on December 23, 2020December 10, 2020

https://www.quantamagazine.org/common-sense-comes-to-computers-20200430/ artificial intelligenceCommon Sense Comes Closer to ComputersThe problem of common-sense reasoning has plagued the field of artificial intelligence for over 50 years. Now a new approach, borrowing from twoContinue readingWhat I Read: Common Sense Computers

What I Read: Tonks Multi-Task Model

By Andrew Fairless on December 22, 2020December 10, 2020

https://medium.com/shoprunner/tonks-building-one-multi-task-model-to-rule-them-all-3e5d020f1f2b Tonks: Building One (Multi-Task) Model to Rule Them All!Co-written by Nicole Carlson and Michael SugimuraMichael SugimuraApr 28 “Tonks is a library that streamlines the training of multi-task PyTorch networks.Continue readingWhat I Read: Tonks Multi-Task Model

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: sub-linear deep learning algorithm

By Andrew Fairless on December 19, 2020December 4, 2020

https://www.kdnuggets.com/2020/03/deep-learning-breakthrough-sub-linear-algorithm-no-gpu.html Deep Learning Breakthrough: a sub-linear deep learning algorithm that does not need a GPU?By Anshumali Shrivastava, Rice University. “Backpropagation is not an efficient algorithm…. The core idea behind theContinue readingWhat I Read: sub-linear deep learning algorithm

What I Read: Introduction to Circuits

By Andrew Fairless on December 18, 2020December 4, 2020

https://distill.pub/2020/circuits/zoom-in/ Zoom In: An Introduction to CircuitsBy studying the connections between neurons, we can find meaningful algorithms in the weights of neural networks. “In contrast to the typical picture ofContinue readingWhat I Read: Introduction to Circuits

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

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