Key trends from NeurIPS 2019

Linking pages

A survivor's guide to Artificial Intelligence courses at Stanford (Updated Feb 2020) https://huyenchip.com/2018/03/30/guide-to-Artificial-Intelligence-Stanford.html 0 comments
Is NeurIPS Getting Too Big? https://thegradient.pub/neurips-2019-too-big/ 0 comments
A bird’s-eye view of modern AI from NeurIPS 2019 – Alex Kolchinski https://alexkolchinski.com/2019/12/30/neurips-2019/ 0 comments

Linked pages

Facebook's Head of AI Says the Field Will Soon ‘Hit the Wall’ | WIRED https://www.wired.com/story/facebooks-ai-says-field-hit-wall/ 518 comments
Graph Convolutional Networks | Thomas Kipf | Google DeepMind http://tkipf.github.io/graph-convolutional-networks/ 28 comments
https://spectrum.ieee.org/tech-talk/robotics/artificial-intelligence/yoshua-bengio-revered-architect-of-ai-has-some-ideas-about-what-to-build-next 18 comments
Yoshua Bengio · From System 1 Deep Learning to System 2 Deep Learning · SlidesLive https://slideslive.com/38921750/from-system-1-deep-learning-to-system-2-deep-learning 3 comments
Blaise Aguera y Arcas · Social Intelligence · SlidesLive https://slideslive.com/38921748/social-intelligence 1 comment
[1902.02476] A Simple Baseline for Bayesian Uncertainty in Deep Learning https://arxiv.org/abs/1902.02476 0 comments
Top 8 trends from ICLR 2019 https://huyenchip.com/2019/05/12/top-8-trends-from-iclr-2019.html 0 comments
A Gentle Introduction to Graph Neural Networks (Basics, DeepWalk, and GraphSage) | by Kung-Hsiang, Huang (Steeve) | Towards Data Science https://towardsdatascience.com/a-gentle-introduction-to-graph-neural-network-basics-deepwalk-and-graphsage-db5d540d50b3 0 comments
What we learned from NeurIPS 2019 data | by Neural Information Processing Systems Conference | Medium https://medium.com/@NeurIPSConf/what-we-learned-from-neurips-2019-data-111ab996462c 0 comments
[1806.07572] Neural Tangent Kernel: Convergence and Generalization in Neural Networks https://arxiv.org/abs/1806.07572 0 comments