A recurrent neural network (RNN) is one of the two broad types of artificial neural network, characterized by direction of the flow of information between...

Bidirectional recurrent neural networks (BRNN) connect two hidden layers of opposite directions to the same output. With this form of generative deep...

Gated recurrent units (GRUs) are a gating mechanism in recurrent neural networks, introduced in 2014 by Kyunghyun Cho et al. The GRU is like a long short-term...

architectures such as deep neural networks, deep belief networks, recurrent neural networks, convolutional neural networks and transformers have been...

cycles or loops, in contrast to recurrent neural networks, which have a bi-directional flow. Modern feedforward networks are trained using the backpropagation...

A residual neural network (also referred to as a residual network or ResNet) is a seminal deep learning model in which the weight layers learn residual...

In machine learning, a neural network (also artificial neural network or neural net, abbreviated ANN or NN) is a model inspired by the structure and function...

the public internet), feedforward neural networks, and transformers. They have superseded recurrent neural network-based models, which had previously...

in parallel (such as in transformers) or sequentially (such as recurrent neural networks). "Soft" weights can change during each runtime, in contrast to...

as recurrent neural networks and convolutional neural networks, renewed interest in ANNs. The 2010s, saw the development of a deep neural network (a neural...