Deep Learning with Yacine on MSNOpinion

What are 1x1 convolutions in deep learning – explained simply

Understand how 1x1 convolutions work and why they’re essential in modern neural network architectures like ResNet and ...
Deep Learning with Yacine on MSN

Inception Net V1 explained: Step-by-step PyTorch implementation

Learn how the Inception Net V1 architecture works and how to implement it from scratch using PyTorch. Perfect for deep ...
Nature

Information Bottleneck in Deep Learning and Neural Networks

The information bottleneck (IB) principle is a powerful information‐theoretic framework that seeks to compress data representations while preserving the information most pertinent to a given task.
Ars Technica

How a stubborn computer scientist accidentally launched the deep learning boom

During my first semester as a computer science graduate student at Princeton, I took COS 402: Artificial Intelligence. Toward the end of the semester, there was a lecture about neural networks. This ...
Quanta Magazine

Novel Architecture Makes Neural Networks More Understandable

“Neural networks are currently the most powerful tools in artificial intelligence,” said Sebastian Wetzel, a researcher at the Perimeter Institute for Theoretical Physics. “When we scale them up to ...
MIT Technology Review

The next generation of neural networks could live in hardware

Researchers have devised a way to make computer vision systems more efficient by building networks out of computer chips’ logic gates. Networks programmed directly into computer chip hardware can ...
MIT Technology Review

A new way to build neural networks could make AI more understandable

The simplified approach makes it easier to see how neural networks produce the outputs they do. A tweak to the way artificial neurons work in neural networks could make AIs easier to decipher.