August 2021 – Andrew Fairless, Ph.D.

What I Read: Advances in TF-Ranking

By Andrew Fairless on August 31, 2021August 17, 2021

https://ai.googleblog.com/2021/07/advances-in-tf-ranking.html Advances in TF-RankingTuesday, July 27, 2021 Posted by Michael Bendersky and Xuanhui Wang, Software Engineers, Google Research“LTR models — unlike standard classification models that classify one item at aContinue readingWhat I Read: Advances in TF-Ranking

What I Read: demystifying graph deep learning

By Andrew Fairless on August 30, 2021August 17, 2021

https://ericmjl.github.io/essays-on-data-science/machine-learning/graph-nets/ An attempt at demystifying graph deep learningEric Ma “There are a ton of great explainers of what graph neural networks are. However, I find that a lot of themContinue readingWhat I Read: demystifying graph deep learning

What I Read: The one data platform to rule them all

By Andrew Fairless on August 26, 2021August 17, 2021

https://leighmariebraswell.substack.com/p/the-one-data-platform-to-rule-them The one data platform to rule them all… but according to whom?An overview of recent data startups based on popular end usersLeigh Marie BraswellJul 20 “…seeing so many “dataContinue readingWhat I Read: The one data platform to rule them all

What I Read: Multi-task Prediction of Organ Dysfunction

By Andrew Fairless on August 25, 2021August 17, 2021

https://ai.googleblog.com/2021/07/multi-task-prediction-of-organ.html Multi-task Prediction of Organ Dysfunction in ICUsThursday, July 22, 2021 “Applying machine learning (ML) to electronic health records (EHRs) has shown promise in predicting clinical outcomes. However, many ofContinue readingWhat I Read: Multi-task Prediction of Organ Dysfunction

What I Read: Not Optimized By Jax, PyTorch, or Tensorflow

By Andrew Fairless on August 24, 2021August 17, 2021

Useful Algorithms That Are Not Optimized By Jax, PyTorch, or Tensorflow Useful Algorithms That Are Not Optimized By Jax, PyTorch, or TensorflowJuly 21 2021Christopher Rackauckas “It turns out that forContinue readingWhat I Read: Not Optimized By Jax, PyTorch, or Tensorflow

What I Read: Why Deep Learning Works

By Andrew Fairless on August 23, 2021August 17, 2021

https://moultano.wordpress.com/2020/10/18/why-deep-learning-works-even-though-it-shouldnt/ Why Deep Learning Works Even Though It Shouldn’tRyan Moulton’s ArticlesRyan Moulton “Stop talking about minima…. Nobody ever trains their model remotely close to convergence…. What really needs further researchContinue readingWhat I Read: Why Deep Learning Works

What I Read: AI-Generating Algorithms, Evolutionary RL

By Andrew Fairless on August 19, 2021July 22, 2021

https://youtu.be/FJJpmxO2Ci8 GECCO2021 – wkspk105 – WS – EvoRL – AI-Generating Algorithms: A Unique Opportunity for the […]AI-Generating Algorithms: A Unique Opportunity for the Evolutionary RL Community (wkspk105, WS – EvoRL)JunContinue readingWhat I Read: AI-Generating Algorithms, Evolutionary RL

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: I Like Notebooks

By Andrew Fairless on August 17, 2021July 22, 2021

https://youtu.be/9Q6sLbz37gk I Like NotebooksOct 28, 2020Jeremy Howard “I like using Jupyter Notebooks… Particularly when combined with nbdev… In this video, I explain why, and explain why I have a differentContinue readingWhat I Read: I Like Notebooks

What I Read: Geometric, Deep Learning

By Andrew Fairless on August 16, 2021July 22, 2021

https://towardsdatascience.com/geometric-foundations-of-deep-learning-94cdd45b451d?gi=d7fa7307aa63 Geometric foundations of Deep LearningGeometric Deep Learning is an attempt for geometric unification of a broad class of ML problems from the perspectives of symmetry and invariance. These principlesContinue readingWhat I Read: Geometric, Deep Learning

Month: August 2021