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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 ...
A study published in npj Computational Materials presents a new AI system that uses computer vision and language processing ...
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A recurrent neural network-based framework to non-linearly model behaviorally relevant neural dynamicsResearchers at University of Southern California and University of Pennsylvania recently introduced a new nonlinear dynamical modeling framework based on recurrent neural networks (RNNs) that ...
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.
Isolation Forest detects anomalies by isolating observations. It builds binary trees (called iTrees) by recursively ...
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.
A new study published in Scientific Reports has introduced a promising diagnostic tool that could dramatically shorten the long wait times many families face when seeking evaluations for autism and ...
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