• LSTM

  • Referenced in 24 articles [sw03373]
  • human brain is a recurrent neural network (RNN): a network of neurons with feedback connections...
  • Evolino

  • Referenced in 17 articles [sw36450]
  • linear search for sequence learning. Current Neural Network learning algorithms are limited in their ability ... dynamical systems. Most supervised gradient-based recurrent neural networks (RNNs) suffer from a vanishing error ... general framework for sequence learning, EVOlution of recurrent systems with LINear outputs (Evolino). Evolino uses...
  • Clockwork RNN

  • Referenced in 6 articles [sw36448]
  • complex dependencies between temporally distant inputs. Recurrent Neural Networks (RNNs) have the ability, in theory ... short-term memory implemented by their recurrent (feedback) connections. However, in practice they are difficult...
  • LSTMVis

  • Referenced in 3 articles [sw27157]
  • Analysis of Hidden State Dynamics in Recurrent Neural Networks. Recurrent neural networks, and in particular ... long short-term 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...
  • CNN-RNN

  • Referenced in 6 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...
  • 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...
  • TopicRNN

  • Referenced in 3 articles [sw36211]
  • TopicRNN: A Recurrent Neural Network with Long-Range 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/TensorFlow-based implementation of modern ... recurrent neural network architectures. It is optimized for fast and reliable training of recurrent neural ... Sequence-chunking based batch training for recurrent; neural networks; Long short-term memory recurrent neural...
  • AntisymmetricRNN

  • Referenced in 2 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...
  • Skip RNN

  • Referenced in 2 articles [sw36445]
  • Learning to Skip State Updates in Recurrent Neural Networks. Recurrent Neural Networks (RNNs) continue...
  • Keras

  • Referenced in 105 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...
  • Lasagne

  • Referenced in 6 articles [sw20936]
  • forward networks such as Convolutional Neural Networks (CNNs), recurrent networks including Long Short-Term 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...
  • ProLanGO

  • Referenced in 2 articles [sw37442]
  • Neural Machine Translation Based on a Recurrent Neural Network. With the development of next generation ... neural machine translation model based on recurrent neural networks to translate ”ProLan” language to ”GOLan...
  • MidiNet

  • Referenced in 2 articles [sw36061]
  • network models for music generation use recurrent neural networks. However, the recent WaveNet model proposed...
  • Conformer

  • Referenced in 2 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...
  • Sockeye

  • Referenced in 2 articles [sw26584]
  • most prominent encoder-decoder architectures: attentional recurrent neural networks, self-attentional 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 Short-Term Memory...