A neural network is a computational machine-learning model that follows the structure of the human brain. It consists of networks of interconnected nodes or neurons to process and learn from data, run ...

In the previous chapter, we learned various strategies to guide AI models 'down the mountain' (optimization algorithms), such ...

Researchers have developed a new tool to more precisely guide cancer treatment. Described in a paper published in Nature ...

Artificial intelligence is now part of our daily lives, with the subsequent pressing need for larger, more complex models.

Neural networks are computing systems designed to mimic both the structure and function of the human brain. Caltech ...

An AI-driven digital-predistortion (DPD) framework can help overcome the challenges of signal distortion and energy ...

Scientists propose a new way of implementing a neural network with an optical system which could make machine learning more sustainable in the future. The researchers at the Max Planck Institute for ...

Understanding the brain's functional architecture is a fundamental challenge in neuroscience. The connections between neurons ...

The initial research papers date back to 2018, but for most, the notion of liquid networks (or liquid neural networks) is a new one. It was “Liquid Time-constant Networks,” published at the tail end ...

A team of astronomers led by Michael Janssen (Radboud University, The Netherlands) has trained a neural network with millions of synthetic black hole data sets. Based on the network and data from the ...