prior – Andrew Fairless, Ph.D.

What I Read: introduction to NumPyro

By Andrew Fairless on September 19, 2022August 22, 2022

https://dfm.io/posts/intro-to-numpyro/ An astronomer’s introduction to NumPyroDan Foreman-MackeyJul 28 2022 “In this post… I’ll focus primarily on providing an introduction to NumPyro, which is a probabilistic programming library that provides anContinue readingWhat I Read: introduction to NumPyro

What I Read: Short Time Series

By Andrew Fairless on September 1, 2022August 3, 2022

https://minimizeregret.com/short-time-series-prior-knowledge Modeling Short Time Series with Prior KnowledgeWhat ‘Including Prior Information’ really looks like.Tim Radtke2019-04-16 “It is generally difficult to model time series when there is insuffient data to modelContinue readingWhat I Read: Short Time Series

What I Read: Generative Modeling by Estimating Gradients

By Andrew Fairless on March 7, 2022January 20, 2022

https://yang-song.github.io/blog/2021/score/ Generative Modeling by Estimating Gradients of the Data DistributionAuthor Yang SongDate May 5, 2021 “This blog post gives a detailed introduction to score-based generative models. We demonstrate that thisContinue readingWhat I Read: Generative Modeling by Estimating Gradients

What I Read: Bayesian Geometry

By Andrew Fairless on February 21, 2022January 20, 2022

https://towardsdatascience.com/on-bayesian-geometry-7755abf9f4d2 On Bayesian GeometryGeometric interpretation of probability distributionsMichael Larionov, PhD “Bayesian inference is based on the fact that we often don’t know the underlying distribution of data, so we needContinue readingWhat I Read: Bayesian Geometry

What I Read: How to assign partial credit on an exam of true-false questions

By Andrew Fairless on November 30, 2021November 16, 2021

https://terrytao.wordpress.com/2016/06/01/how-to-assign-partial-credit-on-an-exam-of-true-false-questions/ How to assign partial credit on an exam of true-false questions?By Terence Tao1 June, 2016Updates on my research and expository papers, discussion of open problems, and other maths-related topics.Continue readingWhat I Read: How to assign partial credit on an exam of true-false questions

What I Read: Bayesian Media Mix Modeling

By Andrew Fairless on October 7, 2021September 21, 2021

Bayesian Media Mix Modeling for Marketing OptimizationBenjamin Vincent2021-09-17 “Fortunately, with Bayesian modeling, we can do better than this! So-called Media Mix Modelling (MMM) can estimate how effective each advertising channelContinue readingWhat I Read: Bayesian Media Mix Modeling

What I Read: Revisiting Sutton’s Bitter Lesson for AI

By Andrew Fairless on February 15, 2021January 18, 2021

https://blog.exxactcorp.com/compute-goes-brrr-revisiting-suttons-bitter-lesson-artificial-intelligence/ Deep LearningCompute Goes Brrr: Revisiting Sutton’s Bitter Lesson for Artificial IntelligenceMarketing, October 27, 2020 “The main driver of AI progress, according to Sutton, is the increasing availability of computeContinue readingWhat I Read: Revisiting Sutton’s Bitter Lesson for AI

What I Read: Bayesian Neural Networks Need Not Concentrate

By Andrew Fairless on December 7, 2020December 13, 2020

https://jacobbuckman.com/2020-01-22-bayesian-neural-networks-need-not-concentrate/ Bayesian Neural Networks Need Not ConcentratePosted on January 22, 2020by Carles Gelada and Jacob Buckman “…it’s important that we, as a field, stop ignoring the crucial importance that theContinue readingWhat I Read: Bayesian Neural Networks Need Not Concentrate

What I Read: The Case for Bayesian Deep Learning

By Andrew Fairless on December 6, 2020December 13, 2020

https://cims.nyu.edu/~andrewgw/caseforbdl/ The Case for Bayesian Deep LearningAndrew Gordon WilsonJanuary 11, 2020 “…ignoring epistemic uncertainty is a key reason that standard neural network training is miscalibrated. By erroneously assuming that theContinue readingWhat I Read: The Case for Bayesian Deep Learning

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