
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...

hebbRNN
 Referenced in 1 article
[sw29194]
 RewardModulated 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 ... biologicallyplausible training rule for recurrent neural networks using a delayed and sparse reward signal...

charrnn
 Referenced in 1 article
[sw27212]
 This code implements multilayer 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...

BioLSTM
 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 (BioLSTM) that can predict...

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

PoPMnet
 Referenced in 1 article
[sw36063]
 Structure Generation Net (SGN) and a Recurrent Neural Network (RNN)based Melody Generation...

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...

CrySSMEx
 Referenced in 1 article
[sw01960]
 extracting Finite State Machines from Recurrent Neural Networks. Input: sequential data generated from RNNs. Output...

Synaptic
 Referenced in 1 article
[sw27138]
 first order or even second order neural network architectures. This library includes a few built ... short term memory networks (LSTM), liquid state machines or Hopfield networks, and a trainer capable ... training any given network, which includes builtin training tasks/tests like solving an XOR, completing ... like training algorithm for secondorder recurrent neural networks...

Ithemal
 Referenced in 1 article
[sw25886]
 Basic Block Throughput Estimation using Deep Neural Networks. Statically estimating the number of processor clock ... uses a novel Directed Acyclic GraphRecurrent Neural Network (DAGRNN) based datadriven approach...

ARGUS framework
 Referenced in 1 article
[sw15168]
 system are based on multidimensional recurrent neural networks (MDRNN) and connectionist temporal classification...

SignalP
 Referenced in 1 article
[sw27722]
 based on a deep convolutional and recurrent neural network architecture including a conditional random field...

OSTSC
 Referenced in 1 article
[sw22352]
 /TKDE.2013.37> and adapted for use with Recurrent Neural Networks implemented in ’TensorFlow...

rnastateinf
 Referenced in 1 article
[sw33162]
 prediction via state inference with deep recurrent neural networks. The problem of determining which nucleotides...

TPALSTM
 Referenced in 1 article
[sw34694]
 data, which can be achieved by recurrent neural networks (RNNs) with an attention mechanism...

DeLS3D
 Referenced in 1 article
[sw36651]
 incorporate temporal information, a multilayer recurrent neural network (RNN) is further deployed improve...

DeepAffinity
 Referenced in 1 article
[sw39160]
 CompoundProtein Affinity through Unified Recurrent and Convolutional Neural Networks. Motivation: Drug discovery demands rapid ... deep learning model that unifies recurrent and convolutional neural networks has been proposed to exploit...

keras
 Referenced in 10 articles
[sw22353]
 Keras’ , a highlevel neural networks ’API’. ’Keras’ was developed with a focus ... fast experimentation, supports both convolution based networks and recurrent networks (as well as combinations...