Nature

Deep Learning and Neural Network Approximations

Deep learning has emerged as a transformative paradigm in modern computational science, leveraging neural networks to approximate complex functions across a variety of domains. Central to this ...
The Scientist

Artificial Neural Networks: Learning by Doing

Article reviewed by Grace Lindsay, PhD from New York University. Scientists design ANNs to function like neurons. 6 They write lines of code in an algorithm such that there are nodes that each contain ...
Centrum Wiskunde & Informatica

ML Seminar Andreas Papachristodoulou (University of Cyprus)

This seminar presents our work on local/layer-wise learning, with a focus on Channel-wise Competitive Learning (CwC), a ...
Nature

Neural Network-Based Branch Prediction Techniques

Neural network-based branch prediction techniques represent a significant advancement in processor architecture, where machine learning models replace traditional, heuristic-based mechanisms to ...
Android Police

Neural Networks: Everything you need to know

Parth is a technology analyst and writer specializing in the comprehensive review and feature exploration of the Android ecosystem. His work is distinguished by its meticulous focus on flagship ...
eWeek

Neural Networks vs. Deep Learning

eSpeaks’ Corey Noles talks with Rob Israch, President of Tipalti, about what it means to lead with Global-First Finance and how companies can build scalable, compliant operations in an increasingly ...
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 ...
eWeek

The Pros and Cons of Deep Learning

eSpeaks’ Corey Noles talks with Rob Israch, President of Tipalti, about what it means to lead with Global-First Finance and how companies can build scalable, compliant operations in an increasingly ...
Quanta Magazine

Neural Networks Need Data to Learn. Even If It’s Fake.

Real data can be hard to get, so researchers are turning to synthetic data to train their artificial intelligence systems. On a sunny day in late 1987, a Chevy van drove down a curvy wooded path on ...
The Conversation

Nobel Prize in physics spotlights key breakthroughs in AI revolution − making machines that learn

Ambuj Tewari receives funding from the NSF. If your jaw dropped as you watched the latest AI-generated video, your bank balance was saved from criminals by a fraud detection system, or your day was ...
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 ...