• TensorFlow

  • Referenced in 206 articles [sw15170]
  • purposes of conducting machine learning and deep neural networks research, but the system is general...
  • darch

  • Referenced in 210 articles [sw11086]
  • publications ”A fast learning algorithm for deep belief nets” (G. E. Hinton, S. Osindero...
  • Keras

  • Referenced in 63 articles [sw15491]
  • Keras: Deep Learning library for Theano and TensorFlow. Keras is a minimalist, highly modular neural ... Keras if you need a deep learning library that: allows for easy and fast prototyping...
  • PyTorch

  • Referenced in 79 articles [sw20939]
  • strong GPU acceleration. PyTorch is a deep learning framework that puts Python first...
  • Caffe

  • Referenced in 42 articles [sw17850]
  • Caffe is a deep learning framework made with expression, speed, and modularity in mind...
  • MXNet

  • Referenced in 19 articles [sw20940]
  • MXNet is a deep learning framework designed for both efficiency and flexibility. It allows ... MXNet is also more than a deep learning project. It is also a collection ... blue prints and guidelines for building deep learning systems, and interesting insights of DL systems...
  • Edward

  • Referenced in 14 articles [sw21517]
  • models on small data sets to complex deep probabilistic models on large data sets. Edward ... three fields: Bayesian statistics and machine learning, deep learning, and probabilistic programming...
  • cuDNN

  • Referenced in 8 articles [sw17848]
  • cuDNN: Efficient Primitives for Deep Learning. We present a library of efficient implementations of deep ... learning primitives. Deep learning workloads are computationally intensive, and optimizing their kernels is difficult ... there is no analogous library for deep learning. Without such a library, researchers implementing deep ... BLAS, with optimized routines for deep learning workloads. Our implementation contains routines for GPUs, although...
  • DeepStack

  • Referenced in 11 articles [sw27097]
  • automatically learned from self-play using deep learning. In a study involving 44,000 hands...
  • Chainer

  • Referenced in 8 articles [sw26707]
  • next-generation open source framework for deep learning. Chainer is a Python-based deep learning...
  • DeepLab

  • Referenced in 11 articles [sw15303]
  • task of semantic image segmentation with Deep Learning and make three main contributions that ... which feature responses are computed within Deep Convolutional Neural Networks. It also allows...
  • PointNet

  • Referenced in 11 articles [sw31209]
  • PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation. Point cloud...
  • pLoc-mGneg

  • Referenced in 23 articles [sw25190]
  • Gram-negative bacterial proteins by deep gene ontology learning via general PseAAC. Information...
  • Tensor2Tensor

  • Referenced in 7 articles [sw26507]
  • short, is a library of deep learning models and datasets designed to make deep learning...
  • OverFeat

  • Referenced in 9 articles [sw17857]
  • ConvNet. We also introduce a novel deep learning approach to localization by learning to predict...
  • FaceNet

  • Referenced in 8 articles [sw21626]
  • present a system, called FaceNet, that directly learns a mapping from face images ... feature vectors. Our method uses a deep convolutional network trained to directly optimize the embedding ... intermediate bottleneck layer as in previous deep learning approaches. To train, we use triplets...
  • CNTK

  • Referenced in 8 articles [sw21056]
  • Toolkit (https://cntk.ai), is a unified deep-learning toolkit that describes neural networks...
  • VAMPnets

  • Referenced in 5 articles [sw32927]
  • VAMPnets: Deep learning of molecular kinetics. There is an increasing demand for computing the relevant ... Markov processes (VAMP) to develop a deep learning framework for molecular kinetics using neural networks...
  • DeepMath

  • Referenced in 7 articles [sw27551]
  • knowledge, this is the first time deep learning has been applied to theorem proving...
  • Dopamine

  • Referenced in 4 articles [sw31151]
  • Research Framework for Deep Reinforcement Learning. Deep reinforcement learning (deep RL) research has grown significantly...