• LSTM

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

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

  • Referenced in 3 articles [sw27203]
  • novel dense localization layer, and Recurrent Neural Network language model that generates the label sequences...
  • 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...
  • Keras

  • Referenced in 89 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...
  • Sockeye

  • Referenced in 2 articles [sw26584]
  • most prominent encoder-decoder architectures: attentional recurrent neural networks, self-attentional transformers, and fully convolutional...
  • CURRENNT

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

  • Referenced in 1 article [sw29194]
  • Reward-Modulated Hebbian Learning Rule for Recurrent Neural Networks. How does our brain learn ... motor skills using neural networks. However, training these networks to produce meaningful behavior has proven ... biologically-plausible training rule for recurrent neural networks using a delayed and sparse reward signal...
  • char-rnn

  • Referenced in 1 article [sw27212]
  • This code implements multi-layer Recurrent Neural Network (RNN, LSTM, and GRU) for training/sampling from ... file as input and trains a Recurrent Neural Network that learns to predict the next...
  • Bio-LSTM

  • Referenced in 1 article [sw25897]
  • LSTM: A Biomechanically Inspired Recurrent Neural Network for 3D Pedestrian Pose and Gait Prediction ... This paper proposes a biomechanically inspired recurrent neural network (Bio-LSTM) that can predict...
  • Leabra7

  • Referenced in 1 article [sw26111]
  • Python package for modeling recurrent, biologically-realistic neural networks. Emergent is a software package that ... algorithm to simulate and train arbitrary recurrent neural network architectures in a biologically-realistic manner ... with Python’s scientific stack. We demonstrate recurrent Leabra7 networks using traditional pattern-association tasks...
  • ConvS2S

  • Referenced in 1 article [sw26536]
  • variable length output sequence via recurrent neural networks. We introduce an architecture based entirely ... convolutional neural networks. Compared to recurrent models, computations over all elements can be fully parallelized...
  • Conformer

  • Referenced in 1 article [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...
  • auDeep

  • Referenced in 1 article [sw27628]
  • representations from audio with deep recurrent neural networks. auDeep is a Python toolkit for deep ... acoustic data. It is based on a recurrent sequence to sequence autoencoder approach which...