Training algorithm breaks barriers to deep physical neural networks Date: December 7, 2023 Source: Ecole Polytechnique Fédérale de Lausanne Summary: Researchers have developed an algorithm to ...

Particle physics may have been an early adopter, but AI has now spread throughout physics. This shouldn’t be too surprising. Physics is data-heavy and computationally intensive, so it benefits from ...

A new technical paper titled “Exploring Neuromorphic Computing Based on Spiking Neural Networks: Algorithms to Hardware” was published by researchers at Purdue University, Pennsylvania State ...

If you rotate an image of a molecular structure, a human can tell the rotated image is still the same molecule, but a machine ...

The resulting neural network achieved accuracy comparable to that of the original. In another experiment, researchers shrunk ResNet-50 by 99% and still saw a top accuracy of 70.55%.

On a more basic level, [Gigante] did just that, teaching a neural network to play a basic driving game with a genetic algorithm. The game consists of a basic top-down 2D driving game.

Artificial neural networks process data in a manner similar to the human brain. Written by eWEEK content and product recommendations are editorially independent. We may make money when you click ...

In 2007, some of the leading thinkers behind deep neural networks organized an unofficial “satellite” meeting at the margins of a prestigious annual conference on artificial intelligence. The ...