
LSTM
 Referenced in 30 articles
[sw03373]
 human brain is a recurrent neural network (RNN): a network of neurons with feedback connections...

Evolino
 Referenced in 19 articles
[sw36450]
 linear search for sequence learning. Current Neural Network learning algorithms are limited in their ability ... dynamical systems. Most supervised gradientbased recurrent neural networks (RNNs) suffer from a vanishing error ... general framework for sequence learning, EVOlution of recurrent systems with LINear outputs (Evolino). Evolino uses...

AntisymmetricRNN
 Referenced in 7 articles
[sw27774]
 AntisymmetricRNN: A Dynamical System View on Recurrent Neural Networks. Recurrent neural networks have gained widespread ... this paper, we draw connections between recurrent networks and ordinary differential equations. A special form...

CNNRNN
 Referenced in 8 articles
[sw28401]
 label Image Classification. While deep convolutional neural networks (CNNs) have shown a great success ... image. In this paper, we utilize recurrent neural networks (RNNs) to address this problem. Combined...

Keras
 Referenced in 183 articles
[sw15491]
 Keras is a minimalist, highly modular neural networks library, written in Python and capable ... minimalism, and extensibility). supports both convolutional networks and recurrent networks, as well as combinations...

LSTMVis
 Referenced in 3 articles
[sw27157]
 Analysis of Hidden State Dynamics in Recurrent Neural Networks. Recurrent neural networks, and in particular ... long shortterm memory (LSTM) networks, are a remarkably effective tool for sequence modeling that ... LSTMVIS, a visual analysis tool for recurrent neural networks with a focus on understanding these...

RNNLIB
 Referenced in 6 articles
[sw07029]
 software library implementing most of the recurrent neural networks used in my work...

Porter
 Referenced in 4 articles
[sw16910]
 three classes. Porter relies on bidirectional recurrent neural networks with shortcut connections, accurate coding ... sequence alignments, second stage filtering by recurrent neural networks, incorporation of long range information...

DenseCap
 Referenced in 5 articles
[sw27203]
 novel dense localization layer, and Recurrent Neural Network language model that generates the label sequences...

Clockwork RNN
 Referenced in 5 articles
[sw36448]
 complex dependencies between temporally distant inputs. Recurrent Neural Networks (RNNs) have the ability, in theory ... shortterm memory implemented by their recurrent (feedback) connections. However, in practice they are difficult...

TopicRNN
 Referenced in 3 articles
[sw36211]
 TopicRNN: A Recurrent Neural Network with LongRange Semantic Dependency. In this paper, we propose ... TopicRNN, a recurrent neural network (RNN)based language model designed to directly capture the global...

RETURNN
 Referenced in 2 articles
[sw26580]
 RWTH extensible training framework for universal recurrent neural networks, is a Theano/TensorFlowbased implementation of modern ... recurrent neural network architectures. It is optimized for fast and reliable training of recurrent neural ... Sequencechunking based batch training for recurrent; neural networks; Long shortterm memory recurrent neural...

Conformer
 Referenced in 4 articles
[sw35794]
 Speech Recognition. Recently Transformer and Convolution neural network (CNN) based models have shown promising results ... Automatic Speech Recognition (ASR), outperforming Recurrent neural networks (RNNs). Transformer models are good at capturing...

Lasagne
 Referenced in 7 articles
[sw20936]
 forward networks such as Convolutional Neural Networks (CNNs), recurrent networks including Long ShortTerm Memory...

Sigfind
 Referenced in 2 articles
[sw17833]
 peptides in human protein sequences using recurrent neural networks. A new approach called Sigfind ... method is based on the bidirectional recurrent neural network architecture. The modifications to this architecture...

Skip RNN
 Referenced in 1 article
[sw36445]
 Learning to Skip State Updates in Recurrent Neural Networks. Recurrent Neural Networks (RNNs) continue...

Point2Sequence
 Referenced in 2 articles
[sw38075]
 with an Attentionbased Sequence to Sequence Network. Exploring contextual information in the local region ... aggregating all area scales using a recurrent neural network (RNN) based encoderdecoder structure, where...

Sockeye
 Referenced in 2 articles
[sw26584]
 most prominent encoderdecoder architectures: attentional recurrent neural networks, selfattentional transformers, and fully convolutional...

PointRNN
 Referenced in 1 article
[sw36644]
 PointRNN: Point Recurrent Neural Network for Moving Point Cloud Processing. In this paper, we introduce ... Point Recurrent Neural Network (PointRNN) for moving point cloud processing. At each time step, PointRNN ... variants of PointRNN, i.e., Point Gated Recurrent Unit (PointGRU) and Point Long ShortTerm Memory...

CURRENNT
 Referenced in 1 article
[sw12814]
 CURRENNT: the Munich opensource CUDA recurrent neural network toolkit. In this article, we introduce ... opensource parallel implementation of deep recurrent neural networks (RNNs) supporting graphics processing units (GPUs...