• darch

  • Referenced in 262 articles [sw11086]
  • deep belief nets : last visit: 01.08.2013). This package is for generating neural networks with many ... fast learning algorithm for deep belief nets” (G. E. Hinton, S. Osindero ... Reducing the dimensionality of data with neural networks” (G. E. Hinton, R. R. Salakhutdinov). This...
  • SNNS

  • Referenced in 12 articles [sw11828]
  • research on and application of neural nets...
  • PDE-Net

  • Referenced in 25 articles [sw36963]
  • Net: Learning PDEs from Data. In this paper, we present an initial attempt to learn ... data. Inspired by the latest development of neural network designs in deep learning, we propose ... Net is to learn differential operators by learning convolution kernels (filters), and apply neural networks ... Residual Neural Network (ResNet). Numerical experiments show that the PDE-Net has the potential...
  • fastai

  • Referenced in 4 articles [sw31223]
  • library simplifies training fast and accurate neural nets using modern best practices. See the fastai...
  • ACMD

  • Referenced in 3 articles [sw02412]
  • ACMD: A practical tool for automatic neural net based learning...
  • DoReFa-Net

  • Referenced in 4 articles [sw36246]
  • DoReFa-Net: Training Low Bitwidth Convolutional Neural Networks with Low Bitwidth Gradients. We propose DoReFa ... Net, a method to train convolutional neural networks that have low bitwidth weights and activations ... bitwidth weights and activations/gradients respectively, DoReFa-Net can use bit convolution kernels to accelerate both ... DoReFa-Net opens the way to accelerate training of low bitwidth neural network on these...
  • V-Net

  • Referenced in 5 articles [sw35860]
  • Net: Fully Convolutional Neural Networks for Volumetric Medical Image Segmentation. Convolutional Neural Networks (CNNs) have...
  • XANNpred

  • Referenced in 1 article [sw16926]
  • XANNpred: Neural nets that predict the propensity of a protein to yield diffraction-quality crystals ... XANNpred is a pair of Artificial Neural Networks (XANNpred-PDB, XANNpred-SG). Proteins with XANNpred ... C.A.J., and Barton, G.J. (2011), XANNpred: Neural nets that predict the propensity of a protein...
  • Minibatch.jl

  • Referenced in 1 article [sw31974]
  • Minibatch.jl: Write neural net code that operates on individual data samples and autobatch it using...
  • pystiche

  • Referenced in 1 article [sw35621]
  • Mahendran & Vedaldi, 2015) as well as neural net architectures (Krizhevsky, Sutskever, & Hinton, 2012; Simonyan & Zisserman...
  • keras-vis

  • Referenced in 1 article [sw34737]
  • visualizing and debugging your trained keras neural net models. Currently supported visualizations include: Activation maximization...
  • PoPMnet

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

  • Referenced in 1 article [sw32923]
  • GXNOR-Net: training deep neural networks with ternary weights and activations without full-precision memory ... under a unified discretization framework. Although deep neural networks (DNNs) are being a revolutionary power ... networks, termed as gated XNOR networks (GXNOR-Nets) since only the event of non-zero...
  • HydraPlus-Net

  • Referenced in 1 article [sw30751]
  • HydraPlus-Net: Attentive Deep Features for Pedestrian Analysis. Pedestrian analysis plays a vital role ... computer vision systems. Despite that the convolutional neural networks are remarkable in learning discriminative features ... attention-based deep neural network, named as HydraPlus-Net (HP-net), that multi-directionally feeds...
  • DeepRED

  • Referenced in 1 article [sw34233]
  • understandable rules from neural networks. However, most authors focus on nets with only one single ... able to extract rules from deep neural networks. The evaluation of the proposed algorithm shows...
  • CNTK

  • Referenced in 10 articles [sw21056]
  • unified deep-learning toolkit that describes neural networks as a series of computational steps ... types such as feed-forward DNNs, convolutional nets (CNNs), and recurrent networks (RNNs/LSTMs). It implements...
  • fbfft

  • Referenced in 3 articles [sw25688]
  • Nets With fbfft: A GPU Performance Evaluation. We examine the performance profile of Convolutional Neural...
  • DeepLab

  • Referenced in 15 articles [sw15303]
  • DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs ... feature responses are computed within Deep Convolutional Neural Networks. It also allows us to effectively...