A review from Xidian University shows that advanced computational algorithms—from neural networks and matrix methods to recommendation engines and ...

Recently, neural network model-based control has received wide interests in kinematics control of manipulators. To enhance learning ability of neural network models, the autoencoder method is used as ...

As the saying goes, we never stop learning. This is especially important in today’s job market, whether you are already enjoying gainful employment or you’re looking for your next gig. That's where ...

For decades, scientists have looked to light as a way to speed up computing. Photonic neural networks—systems that use light instead of electricity to process information—promise faster speeds and ...

Aimed at AI/ML applications, Renesas’ RA8P1 MCUs leverage an Arm Ethos-U55 neural processing unit (NPU) delivering 256 GOPS ...

Recent brain-computer-interface (BCI) devices have made it possible to translate neural activity directly into text and even speech. Unfortunately, these systems had significant latency, often ...

Researchers at University of Southern California and University of Pennsylvania recently introduced a new nonlinear dynamical modeling framework based on recurrent neural networks (RNNs) that ...

Isolation Forest detects anomalies by isolating observations. It builds binary trees (called iTrees) by recursively ...

Neuroscientists want to understand how individual neurons encode information that allows us to distinguish objects, like telling a leaf apart from a rock. But they have struggled to build ...

Celebrity chef and Food Network star Anne Burrell died unexpectedly Tuesday. She was 55.

Complex networks articles from across Nature Portfolio Complex networks are networks that feature patterns of connection between their elements that are neither purely regular nor purely random.