2022 – Page 15 – Andrew Fairless, Ph.D.

What I Read: Gaussian Process, Active Learning in Physics

By Andrew Fairless on January 17, 2022December 11, 2021

https://towardsdatascience.com/gaussian-process-first-step-towards-active-learning-in-physics-239a8b260579?gi=41cc7e15ddd0 Gaussian Process: First Step Towards Active Learning in PhysicsMaxim ZiatdinovNov 1 “An approach to address these problems is a Gaussian Process…. we would like to offer a slightly unusualContinue readingWhat I Read: Gaussian Process, Active Learning in Physics

What I Read: Exploring beauty of pure mathematics

By Andrew Fairless on January 12, 2022December 11, 2021

https://deepmind.com/blog/article/exploring-the-beauty-of-pure-mathematics-in-novel-ways Exploring the beauty of pure mathematics in novel ways01 Dec 2021Alex Davies, Pushmeet Kohli, Demis Hassabis “…we explored the potential of machine learning (ML) to recognize mathematical structures andContinue readingWhat I Read: Exploring beauty of pure mathematics

What I Read: Neural-Control Family

By Andrew Fairless on January 10, 2022December 11, 2021

https://www.gshi.me/blog/NeuralControl/ Neural-Control Family: What Deep Learning + Control Enables in the Real WorldGuanya Shi “…is machine learning (especially deep learning) really ready to be deployed in safety-critical systems?”

What I Read: Maps of Model Space, Stan

By Andrew Fairless on January 5, 2022December 11, 2021

https://statmodeling.stat.columbia.edu/2021/11/19/drawing-maps-of-model-space-with-modular-stan/ Drawing Maps of Model Space with Modular StanPosted on November 19, 2021 9:50 AM by AndrewThis post is by Ryan Bernstein. “What if instead of describing one model atContinue readingWhat I Read: Maps of Model Space, Stan

What I Read: AntiPatterns, MLOps

By Andrew Fairless on January 4, 2022December 11, 2021

https://arxiv.org/abs/2107.00079 Using AntiPatterns to avoid MLOps MistakesNikhil Muralidhar, Sathappah Muthiah, Patrick Butler, Manish Jain, Yu Yu, Katy Burne, Weipeng Li, David Jones, Prakash Arunachalam, Hays ‘Skip’ McCormick, Naren Ramakrishnan “HereContinue readingWhat I Read: AntiPatterns, MLOps

What I Read: Graph Neural Networks, Differential Geometry, Algebraic Topology

By Andrew Fairless on January 3, 2022December 11, 2021

https://towardsdatascience.com/graph-neural-networks-through-the-lens-of-differential-geometry-and-algebraic-topology-3a7c3c22d5f Graph Neural Networks through the lens of Differential Geometry and Algebraic TopologyMichael Bronstein “Differential geometry and algebraic topology are not encountered very frequently in mainstream machine learning… tools fromContinue readingWhat I Read: Graph Neural Networks, Differential Geometry, Algebraic Topology

Year: 2022