Artificial neural networks have been applied to problems ... we can make the network 'learn' to solve many types of problems. A model neuron is referred to as a threshold unit and its function ...

Just as GPUs once eclipsed CPUs for AI workloads, Neural Processing Units (NPUs) are set to challenge GPUs by delivering even ...

[Ramin Hasani] and colleague [Mathias Lechner] have been working with a new type of Artificial Neural Network called Liquid Neural Networks, and presented some of the exciting results at a recent ...

Traditional artificial intelligence (AI) systems are built on artificial neural networks that mimic the human brain’s neurons ...

Two new neural network designs promise to make AI models more adaptable and efficient, potentially changing how artificial ...

A collaborative team of researchers from Carnegie Mellon University and the University of Pittsburgh designed a clever experiment using a brain-controlled interface to determine whether one-way ...

Morphological profiling allows accurate identification of cell types in dense iPSC-derived cultures, allowing its use for quality control and differentiation monitoring.

This article establishes a neural network-based technique for automatic peak picking in 2D NMR spectroscopy, demonstrating a ...

Researchers applied the mathematical theory of synchronization to clarify how recurrent neural networks (RNNs) generate predictions, revealing a certain map, based on the generalized synchronization, ...