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

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

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: Exploring Bayesian Optimization

By Andrew Fairless on December 26, 2020December 13, 2020

https://distill.pub/2020/bayesian-optimization/ Exploring Bayesian OptimizationBreaking Bayesian Optimization into small, sizeable chunks.AuthorsApoorv AgnihotriIndian Insitute of Technology GandhinagarNipun BatraIndian Insitute of Technology GandhinagarPublishedMay 5, 2020DOI10.23915/distill.00026 “Many modern machine learning algorithms have a largeContinue readingWhat I Read: Exploring Bayesian Optimization

What I Read: Artificial Intelligence Will Do What We Ask

By Andrew Fairless on December 9, 2020November 29, 2020

https://www.quantamagazine.org/artificial-intelligence-will-do-what-we-ask-thats-a-problem-20200130/ artificial intelligenceArtificial Intelligence Will Do What We Ask. That’s a Problem.Natalie WolchoverSenior Writer/EditorJanuary 30, 2020By teaching machines to understand our true desires, one scientist hopes to avoid the potentiallyContinue readingWhat I Read: Artificial Intelligence Will Do What We Ask

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

Tag: Bayesian