• darch

  • Referenced in 138 articles [sw11086]
  • publications ”A fast learning algorithm for deep belief nets” (G. E. Hinton, S. Osindero...
  • TensorFlow

  • Referenced in 113 articles [sw15170]
  • purposes of conducting machine learning and deep neural networks research, but the system is general...
  • Keras

  • Referenced in 33 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 31 articles [sw20939]
  • strong GPU acceleration. PyTorch is a deep learning framework that puts Python first...
  • Caffe

  • Referenced in 30 articles [sw17850]
  • Caffe is a deep learning framework made with expression, speed, and modularity in mind...
  • MXNet

  • Referenced in 15 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...
  • cuDNN

  • Referenced in 7 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...
  • Edward

  • Referenced in 9 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...
  • pLoc-mGneg

  • Referenced in 20 articles [sw25190]
  • Gram-negative bacterial proteins by deep gene ontology learning via general PseAAC. Information...
  • Tensor2Tensor

  • Referenced in 5 articles [sw26507]
  • short, is a library of deep learning models and datasets designed to make deep learning...
  • CNTK

  • Referenced in 7 articles [sw21056]
  • Toolkit (https://cntk.ai), is a unified deep-learning toolkit that describes neural networks...
  • Geometer's Sketchpad

  • Referenced in 218 articles [sw04858]
  • through college—a tangible, visual way to learn mathematics that increases their engagement, understanding ... functions—from linear to trigonometric—promoting deep understanding. Sketchpad is the optimal tool for interactive...
  • DeepMath

  • Referenced in 6 articles [sw27551]
  • knowledge, this is the first time deep learning has been applied to theorem proving...
  • Chainer

  • Referenced in 4 articles [sw26707]
  • next-generation open source framework for deep learning. Chainer is a Python-based deep learning...
  • OverFeat

  • Referenced in 5 articles [sw17857]
  • ConvNet. We also introduce a novel deep learning approach to localization by learning to predict...
  • GAN Lab

  • Referenced in 2 articles [sw27149]
  • Interactive Visual Experimentation. Recent success in deep learning has generated immense interest among practitioners ... developed to help people more easily learn deep learning, most existing tools focus on simpler ... GANs), a popular class of complex deep learning models. With GAN Lab, users can interactively ... interactive experimentation features for learning complex deep learning models, such as step-by-step training...
  • DeepStack

  • Referenced in 4 articles [sw27097]
  • automatically learned from self-play using deep learning. In a study involving 44,000 hands...
  • ZhuSuan

  • Referenced in 2 articles [sw27939]
  • python probabilistic programming library for Bayesian deep learning, which conjoins the complimentary advantages of Bayesian ... methods and deep learning. ZhuSuan is built upon Tensorflow. Unlike existing deep learning libraries, which ... networks and supervised tasks, ZhuSuan provides deep learning style primitives and algorithms for building probabilistic...
  • maxDNN

  • Referenced in 2 articles [sw19846]
  • maxDNN: An Efficient Convolution Kernel for Deep Learning with Maxwell GPUs. This paper describes maxDNN ... computationally efficient convolution kernel for deep learning with the NVIDIA Maxwell GPU. maxDNN reaches ... computational efficiency on typical deep learning network architectures. The design combines ideas from cuda-convnet2...
  • DeCAF

  • Referenced in 11 articles [sw17856]
  • conduct experimentation with deep representations across a range of visual concept learning paradigms...