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GRU explained | How gated recurrent units work

Gated Recurrent Unit (GRU) is a type of Recurrent Neural Network (RNN) which performs better than Simple RNN while dealing ...
IEEE

A Novel Adaptive Recurrent Neural Network-Based Control Strategy for Type 3 WF to Mitigate Subsynchronous Interactions

Abstract: The interaction between the wind farm (WF) and the series-compensated long transmission line may cause subsynchronous interaction (SSI) phenomenon. The conventional subsynchronous damping ...
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What Is An Rnn? Recurrent Neural Networks Made Simple

in this video, we will understand what is Recurrent Neural Network in Deep Learning. Recurrent Neural Network in Deep Learning is a model that is used for Natural Language Processing tasks. It can be ...
Frontiers

NeuralConstraints: integrating a neural generative model with constraint-based composition

We present ‘NeuralConstraints,’ a suite of computer-assisted composition tools that integrates a feedforward neural network as a rule within a constraint-based composition framework.
Wired

Liquid AI Is Redesigning the Neural Network

Artificial intelligence might now be solving advanced math, performing complex reasoning, and even using personal computers, but today’s algorithms could still learn a thing or two from microscopic ...
eLife

When and why does motor preparation arise in recurrent neural network models of motor control?

This important study provides a new perspective on why preparatory activity occurs before the onset of movement. The authors report that when there is a cost on the inputs, the optimal inputs should ...
PNAS

Input-driven circuit reconfiguration in critical recurrent neural networks

The brain has numerous mechanisms to modify its own circuitry. But physical alterations take time, and we have long known that interactions between neurons can change in fractions of a second during a ...