• Keras

  • Referenced in 120 articles [sw15491]
  • Keras: Deep Learning library for Theano and TensorFlow. Keras is a minimalist, highly modular neural ... doing good research. Use Keras if you need a deep learning library that: allows ... Read the documentation at Keras.io. Keras is compatible with: Python...
  • keras

  • Referenced in 8 articles [sw22353]
  • package keras: R Interface to ’Keras’. Interface to ’Keras, a high-level neural ... networks ’API’. ’Keras’ was developed with a focus on enabling fast experimentation, supports both convolution...
  • AutoKeras

  • Referenced in 5 articles [sw33648]
  • AutoKeras, Auto-Keras: An Efficient Neural Architecture Search System. Neural architecture search (NAS) has been ... system based on our method, namely Auto-Keras. The system runs in parallel...
  • geomstats

  • Referenced in 3 articles [sw24373]
  • computing backends such as numpy, tensorflow and keras. We have enabled GPU implementation and integrated ... geomstats manifold computations into keras deep learning framework. This paper also presents a review...
  • SciANN

  • Referenced in 3 articles [sw38344]
  • widely used deep-learning packages TensorFlow and Keras to build deep neural networks and optimization ... models, thus inheriting many of Keras’s functionalities, such as batch optimization and model reuse...
  • keras-rl

  • Referenced in 2 articles [sw35087]
  • keras-rl implements some state-of-the art deep reinforcement learning algorithms in Python ... seamlessly integrates with the deep learning library Keras...
  • keras-vis

  • Referenced in 1 article [sw34737]
  • keras-vis: Keras visualization toolkit. keras-vis is a high-level toolkit for visualizing ... debugging your trained keras neural net models. Currently supported visualizations include: Activation maximization; Saliency maps...
  • Keras-GAN

  • Referenced in 1 article [sw32552]
  • Keras-GAN: Collection of Keras implementations of Generative Adversarial Networks (GANs) suggested in research papers...
  • Foolbox

  • Referenced in 2 articles [sw20935]
  • popular deep learning frameworks such as PyTorch, Keras, TensorFlow, Theano and MXNet, provides a straight...
  • DeepTrade_keras

  • Referenced in 1 article [sw34679]
  • DeepTrade - keras version. Could deep learning help us with buying and selling stocks in market...
  • Comet.ml

  • Referenced in 1 article [sw27031]
  • hyper parameters, metrics, code, stdout tracking. Supports Keras, Tensorflow, PyTorch, scikit-learn...
  • MLaut

  • Referenced in 1 article [sw27171]
  • interfaces to the scikit-learn and keras modelling libraries. Experiments are easy...
  • DeepArchitect

  • Referenced in 1 article [sw31717]
  • framework. Currently, we support Tensorflow, Keras, and PyTorch. See here for minimal complete examples...
  • DALEXtra

  • Referenced in 1 article [sw35212]
  • those created using ’python’ ’scikit-learn’ and ’keras’ libraries, and ’java’ ’h2o’ library. Important part...
  • ART

  • Referenced in 1 article [sw37566]
  • supports all popular machine learning frameworks (TensorFlow, Keras, PyTorch, MXNet, scikit-learn, XGBoost, LightGBM, CatBoost...
  • PDE-NetGen

  • Referenced in 1 article [sw37737]
  • based implementations of PDE solvers using Keras. With some knowledge of a problem, PDE-NetGen...
  • GPflux

  • Referenced in 1 article [sw38081]
  • with and built on top of the Keras deep learning eco-system. This enables practitioners...
  • AlphaPy

  • Referenced in 1 article [sw38192]
  • machine learning models using scikit-learn, Keras, xgboost, LightGBM, and CatBoost. Generate blended or stacked...
  • NxTF

  • Referenced in 1 article [sw38430]
  • developed NxTF: a programming interface derived from Keras and compiler optimized for mapping deep convolutional...