人工智能2021 · 分享于 Hacker News

Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges

探索《Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges》的原文与 Hacker News 社区讨论,查看来源并加入阅读清单。

阅读原文

看看社区如何讨论这个想法。

来自 Hacker News 的原始讨论。不同的视角、疑问,以及值得继续思考的线索。

最多展示 100 条相关讨论。论文可能出现在评论中,并非原帖投稿内容。

在讨论中发现的引用

按 HN 条目顺序展示最近的 50 条引用来源。

Ygpjt ·

The maths you need to start understanding LLMs

616 赞同120 评论
Ysicp-enjoyer ·

Why train when you can optimize?

182 赞同68 评论
Yoccamschainsaw ·

Just know stuff. (Or, how to achieve success in a machine learning PhD)

27 赞同3 评论
YArtWomb ·

An Erlangen Programme to Establish the Geometric Foundations of Deep Learning

22 赞同5 评论
Yrkp8000 ·

Spherical CNNs (2018)

22 赞同3 评论
Ymfrieswyk ·

Ask HN: What are the foundational texts for learning about AI/ML/NN?

14 赞同6 评论
Ymariuz ·

Understanding and Coding the Self-Attention Mechanism of Large Language Models

4 赞同0 评论
YAnon84 ·

Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges

3 赞同1 评论
Yibobev ·

Geometric Deep Learning Grids, Groups, Graphs, Geodesics, and Gauges [pdf]

3 赞同0 评论
YMAXPOOL ·

Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges

2 赞同0 评论
Ymindcrime ·

Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges

2 赞同0 评论
YAnon84 ·

Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges

2 赞同0 评论
Ydplarson ·

ICLR 2021 Keynote: “Geometric Deep Learning: The Erlangen Programme of ML”

1 赞同1 评论

一个想法,引向另一个。

发现更多论文