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 ...

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 ...

Neural networks first treat sentences like puzzles solved by word order, but once they read enough, a tipping point sends ...

Scientists at UCSF combined advanced brain-network modeling, genetics, and imaging to reveal how tau protein travels through ...

An NYU team uses machine learning to analyze neural activity data and uncover how speech is produced. In a recent paper ...

A study published in npj Computational Materials presents a new AI system that uses computer vision and language processing ...

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 ...

Microsoft’s artificial intelligence tool BioEmu can predict the multiple conformational states of a protein, giving insight into how a protein moves and its potential function.

GREmLN leverages a graph-based architecture to represent gene-gene interactions to predict cell behavior for therapeutic ...

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.