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

What I Read: Diffusion Models

By Andrew Fairless on August 18, 2021July 22, 2021

https://lilianweng.github.io/lil-log/2021/07/11/diffusion-models.html#nice What are Diffusion Models?Jul 11, 2021Lilian Weng“Diffusion models are inspired by non-equilibrium thermodynamics…. Unlike VAE or flow models, diffusion models are learned with a fixed procedure and the latentContinue readingWhat I Read: Diffusion Models

What I Read: Parallel Bayesian Optimization

By Andrew Fairless on May 24, 2021May 1, 2021

https://medium.com/riskified-technology/from-sequential-to-parallel-a-story-about-parallel-bayesian-hyperparameter-optimization-f124ed29f556 From Sequential to Parallel, a story about Bayesian Hyperparameter OptimizationAndres AsaraviciusApr 26 “The goal of this process is to find the best set of parameters, and our goal wasContinue readingWhat I Read: Parallel Bayesian Optimization

What I Read: Bayesian and frequentist results

By Andrew Fairless on May 21, 2021May 1, 2021

https://www.allendowney.com/blog/2021/04/25/bayesian-and-frequentist-results-are-not-the-same-ever/ Bayesian and frequentist results are not the same, everApril 25, 2021Allen Downey “You can’t compare results from Bayesian and frequentist methods because the results are different kinds of things….Continue readingWhat I Read: Bayesian and frequentist results

What I Read: Bayesian Hierarchical Modelling at Scale

By Andrew Fairless on April 2, 2021March 21, 2021

https://florianwilhelm.info/2020/10/bayesian_hierarchical_modelling_at_scale/ Finally! Bayesian Hierarchical Modelling at ScaleFlorian WilhelmDate Oct. 01, 2020 “In this blog post, I want to draw your attention to the somewhat dusty Bayesian Hierarchical Modelling. Modern techniquesContinue readingWhat I Read: Bayesian Hierarchical Modelling at Scale

What I Read: Neural Text Generation

By Andrew Fairless on March 11, 2021March 7, 2021

https://lilianweng.github.io/lil-log/2021/01/02/controllable-neural-text-generation.html Controllable Neural Text GenerationJan 2, 2021Lilian Weng “How to steer a powerful unconditioned language model? In this post, we will delve into several approaches for controlled content generation withContinue readingWhat I Read: Neural Text Generation

What I Watch: The medical test paradox, Can redesigning Bayes rule help?

By Andrew Fairless on February 28, 2021February 27, 2021

https://youtu.be/lG4VkPoG3ko The medical test paradox: Can redesigning Bayes rule help?Dec 22, 20203Blue1Brown “In short, an accurate test is not necessarily a predictive test… of all of the places for mathContinue readingWhat I Watch: The medical test paradox, Can redesigning Bayes rule help?

What I Read: Bayesian Product Ranking

By Andrew Fairless on January 22, 2021December 30, 2020

https://tech.wayfair.com/data-science/2020/01/bayesian-product-ranking-at-wayfair/ Bayesian Product Ranking at WayfairJanuary 20, 2020 “If we are not able to personalize a customer’s experience, for example, because they are a first-time customer and we do notContinue readingWhat I Read: Bayesian Product Ranking

What I Read: Continual Learning… and the Bridge to Active and Open World Learning

By Andrew Fairless on January 22, 2021December 30, 2020

https://arxiv.org/abs/2009.01797 A Wholistic View of Continual Learning with Deep Neural Networks: Forgotten Lessons and the Bridge to Active and Open World LearningMartin Mundt, Yong Won Hong, Iuliia Pliushch, Visvanathan RameshContinue readingWhat I Read: Continual Learning… and the Bridge to Active and Open World Learning

What I Read: Think Like an Epidemiologist

By Andrew Fairless on January 16, 2021December 24, 2020

https://www.nytimes.com/2020/08/04/science/coronavirus-bayes-statistics-math.html How to Think Like an EpidemiologistDon’t worry, a little Bayesian analysis won’t hurt you.By Siobhan RobertsAug. 4, 2020Updated 4:57 p.m. ET “Observing early research in March about how theContinue readingWhat I Read: Think Like an Epidemiologist

What I Read: A winner’s curse adjustment

By Andrew Fairless on January 10, 2021December 23, 2020

http://www.erikdrysdale.com/winners_curse/ Erik DrysdalebioeconometRicianAbout Recent Posts ShinyApps CVA winner’s curse adjustment for a single test statistic “One consequence of using frequentist statistical tools to conduct scientific inference is that effect sizesContinue readingWhat I Read: A winner’s curse adjustment

Tag: Bayesian