• BinaryConnect

  • Referenced in 24 articles [sw35871]
  • BinaryConnect: Training Deep Neural Networks with binary weights during propagations. Deep Neural Networks (DNN) have ... components of the digital implementation of neural networks. We introduce BinaryConnect, a method which consists...
  • Reluplex

  • Referenced in 20 articles [sw31367]
  • Efficient SMT Solver for Verifying Deep Neural Networks. Deep neural networks have emerged ... technique for verifying properties of deep neural networks (or providing counter-examples). The technique ... crucial ingredient in many modern neural networks. The verification procedure tackles neural networks ... technique on a prototype deep neural network implementation of the next-generation airborne collision avoidance...
  • BinaryNet

  • Referenced in 21 articles [sw35872]
  • Binarized Neural Networks: Training Deep Neural Networks with Weights and Activations Constrained ... introduce a method to train Binarized Neural Networks (BNNs) - neural networks with binary weights...
  • DeepLab

  • Referenced in 36 articles [sw15303]
  • responses are computed within Deep Convolutional Neural Networks. It also allows us to effectively enlarge...
  • SSD

  • Referenced in 32 articles [sw26652]
  • images using a single deep neural network. Our approach, named SSD, discretizes the output space...
  • Xception

  • Referenced in 22 articles [sw39068]
  • interpretation of Inception modules in convolutional neural networks as being an intermediate step in-between ... propose a novel deep convolutional neural network architecture inspired by Inception, where Inception modules have...
  • LSTM

  • Referenced in 30 articles [sw03373]
  • human brain is a recurrent neural network (RNN): a network of neurons with feedback connections...
  • XNOR-Net

  • Referenced in 21 articles [sw39593]
  • ImageNet Classification Using Binary Convolutional Neural Networks. We propose two efficient approximations to standard convolutional ... neural networks: Binary-Weight-Networks and XNOR-Networks. In Binary-Weight-Networks, the filters...
  • MobileNets

  • Referenced in 21 articles [sw39590]
  • MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications. We present a class of efficient ... convolutions to build light weight deep neural networks. We introduce two simple global hyper-parameters...
  • ART 3

  • Referenced in 27 articles [sw08755]
  • distributed pattern recognition codes in a neural network hierarchy is introduced. The search process functions...
  • SegNet

  • Referenced in 27 articles [sw27575]
  • novel and practical deep fully convolutional neural network architecture for semantic pixel-wise segmentation termed...
  • Evolino

  • Referenced in 19 articles [sw36450]
  • linear search for sequence learning. Current Neural Network learning algorithms are limited in their ability ... systems. Most supervised gradient-based recurrent neural networks (RNNs) suffer from a vanishing error signal...
  • NETT

  • Referenced in 15 articles [sw41773]
  • NETT: Solving Inverse Problems with Deep Neural Networks. Recovering a function or high-dimensional parameter ... novel algorithms using deep learning and neural networks for inverse problems appeared. While still ... regularizer defined by a trained neural network. We derive well-posedness results and quantitative error ... different from any previous work using neural networks for solving inverse problems. A possible data...
  • FUNFITS

  • Referenced in 26 articles [sw02191]
  • gotten from CRAN (www.cran.r-project.org). The rest -- neural networks, global and local Lyapunov exponents -- is here...
  • MatConvNet

  • Referenced in 18 articles [sw15651]
  • MatConvNet – convolutional neural networks for MATLAB. MatConvNet is an open source implementation of Convolutional Neural...
  • faraway

  • Referenced in 24 articles [sw04357]
  • trees, and even the use of neural networks in statistics. To demonstrate the interplay...
  • DeepFool

  • Referenced in 14 articles [sw20937]
  • accurate method to fool deep neural networks. State-of-the-art deep neural networks have ... efficiently compute perturbations that fool deep networks, and thus reliably quantify the robustness of these ... accurate method to fool deep neural networks...
  • CliffMath

  • Referenced in 23 articles [sw04955]
  • limited to, wireless communications, neural networks, electrical circuits, transportation, and the world wide web. Examples...
  • nnet

  • Referenced in 16 articles [sw07922]
  • package nnet: Feed-forward Neural Networks and Multinomial Log-Linear Models. Software for feed-forward ... neural networks with a single hidden layer, and for multinomial log-linear models...
  • DeepFace

  • Referenced in 22 articles [sw21625]
  • representation from a nine-layer deep neural network. This deep network involves more than...