Neural Networks, Manifolds, and Topology -- colah's blog
Recently, there’s been a great deal of excitement and interest in deep neural networks because they’ve achieved breakthrough results in areas such as computer vision.1
Neural Networks, Manifolds, and Topology -- colah's blog Neural Networks, Manifolds, and Topology Posted on April 6, 2014 topology, neural networks, deep learning, manifold hypothesis Recently, there’s been a great deal of excitement and interest in deep neural networks because they’ve achieved breakthrough results in areas such as computer vision. 1 However, there remain a number of concerns about them. One is that it can be quite challenging to understand what a neural network is really doing. If one trains it well, it achieves high quality results, but it is challenging to understand how it
Explore this link on the map →saved by
- Winnie Xu
- Klaudia U.
- Chloe Chia
- Tasha Pais
- Rona Wang
- Karthik Singh
- Aaron Pham
- Laerdon Kim
- Lydia Nottingham
- Noah T
- Ada Ge
- Julian H
related reading
- Zoom In: An Introduction to Circuitsdistill.pub
- Neural Networks, Types, and Functional Programming -- colah's blogcolah.github.io
- Toy Models of Superpositiontransformer-circuits.pub
- The World Inside Neural Networksgoodfire.ai
- Feature Visualizationdistill.pub
- Neural networks and deep learningneuralnetworksanddeeplearning.com
- Home - colah's blogcolah.github.io
- A Recipe for Training Neural Networkskarpathy.github.io
- Visualizing Neural Networks with the Grand Tourdistill.pub
- Aman's AI Journal • Primers • Ilya Sutskever's Top 30aman.ai
- Neural network training makes beautiful fractals | Jascha’s blogsohl-dickstein.github.io
- [2604.21691] There Will Be a Scientific Theory of Deep Learningarxiv.org