physics – Andrew Fairless, Ph.D.

What I Read: Understanding Moments

By Andrew Fairless on December 21, 2023November 7, 2023

https://gregorygundersen.com/blog/2020/04/11/moments/ Understanding MomentsGregory Gundersen11 April 2020 “Why are a distribution’s moments called “moments”? How does the equation for a moment capture the shape of a distribution? Why do we typicallyContinue readingWhat I Read: Understanding Moments

What I Read: Physical Process, Generative AI

By Andrew Fairless on October 31, 2023October 5, 2023

https://www.quantamagazine.org/new-physics-inspired-generative-ai-exceeds-expectations-20230919/ The Physical Process That Powers a New Type of Generative AISteve Nadis9/19/23 10:15 AM “Some modern image generators rely on the principles of diffusion to create images. Alternatives basedContinue readingWhat I Read: Physical Process, Generative AI

What I Read: Sparse Networks

By Andrew Fairless on July 31, 2023June 15, 2023

https://www.quantamagazine.org/sparse-neural-networks-point-physicists-to-useful-data-20230608/ Sparse Networks Come to the Aid of Big PhysicsSteve NadisJune 8, 2023 “A novel type of neural network is helping physicists with the daunting challenge of data analysis.”

What I Read: Poisson Flow Generative Models

By Andrew Fairless on January 5, 2023November 5, 2022

https://www.assemblyai.com/blog/an-introduction-to-poisson-flow-generative-models/ An Introduction to Poisson Flow Generative ModelsRyan O’ConnorDeveloper EducatorOct 26, 2022 “Poisson Flow Generative Models (PFGMs) are a new type of generative Deep Learning model, taking inspiration from physicsContinue readingWhat I Read: Poisson Flow Generative Models

What I Read: Make the Universe Think

By Andrew Fairless on July 13, 2022June 27, 2022

https://www.quantamagazine.org/how-to-make-the-universe-think-for-us-20220531/ How to Make the Universe Think for UsCharlie WoodStaff WriterMay 31, 2022 “Physicists are building neural networks out of vibrations, voltages and lasers, arguing that the future of computingContinue readingWhat I Read: Make the Universe Think

What I Read: ‘Machine Scientists’ Distill the Laws of Physics From Raw Data

By Andrew Fairless on June 7, 2022May 23, 2022

https://www.quantamagazine.org/machine-scientists-distill-the-laws-of-physics-from-raw-data-20220510/ Powerful ‘Machine Scientists’ Distill the Laws of Physics From Raw DataCharlie WoodStaff WriterMay 10, 2022 “Researchers say we’re on the cusp of “GoPro physics,” where a camera can pointContinue readingWhat I Read: ‘Machine Scientists’ Distill the Laws of Physics From Raw Data

What I Read: Beyond Message Passing, Graph Neural Networks

By Andrew Fairless on June 6, 2022May 23, 2022

https://thegradient.pub/graph-neural-networks-beyond-message-passing-and-weisfeiler-lehman/ Beyond Message Passing: a Physics-Inspired Paradigm for Graph Neural NetworksMichael Bronstein07.May.2022 “…the “node and edge-centric” mindset of current graph deep learning schemes imposes strong limitations… we propose physics-inspired “continuous”Continue readingWhat I Read: Beyond Message Passing, Graph Neural Networks

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: Does Time Really Flow?

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

https://www.quantamagazine.org/does-time-really-flow-new-clues-come-from-a-century-old-approach-to-math-20200407/ theoretical physicsDoes Time Really Flow? New Clues Come From a Century-Old Approach to Math.The laws of physics imply that the passage of time is an illusion. To avoid thisContinue readingWhat I Read: Does Time Really Flow?

Tag: physics