• PDE-Net

  • Referenced in 63 articles [sw36963]
  • Network-In-Network (NIN) and Residual Neural Network (ResNet). Numerical experiments show that...
  • Inception-v4

  • Referenced in 24 articles [sw39592]
  • Impact of Residual Connections on Learning. Very deep convolutional networks have been central ... There is also some evidence of residual Inception networks outperforming similarly expensive Inception networks without ... architectures for both residual and non-residual Inception networks. These variations improve the single-frame ... stabilizes the training of very wide residual Inception networks. With an ensemble of three residual...
  • PREvaIL

  • Referenced in 10 articles [sw25073]
  • approach for inferring catalytic residues using sequence, structural, and network features in a machine-learning ... multiple levels, including sequence, structure, and residue-contact network, in a random forest machine-learning ... significantly improve the performance of catalytic residue prediction. We believe that this new method...
  • DnCNN

  • Referenced in 45 articles [sw39678]
  • Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising. Discriminative model learning ... construction of feed-forward denoising convolutional neural networks (DnCNNs) to embrace the progress in very ... regularization method into image denoising. Specifically, residual learning and batch normalization are utilized to speed...
  • lvnet

  • Referenced in 4 articles [sw19428]
  • network modeling; LNM) or between residuals (residual network modeling...
  • CATBox

  • Referenced in 4 articles [sw18663]
  • graph, and additional auxiliary graphs like residual networks, are displayed and provide visual feedback...
  • GNMT

  • Referenced in 28 articles [sw26579]
  • LSTM network with 8 encoder and 8 decoder layers using attention and residual connections...
  • PDNET

  • Referenced in 40 articles [sw04752]
  • this algorithm for solving the minimum-cost network flow problem. In each iteration, the linear ... inexactly, and the norm of the resulting residual vector is used in the stopping criteria ... large set of standard minimum-cost network flow test problems. Computational results indicate that...
  • MultiPoseNet

  • Referenced in 2 articles [sw39258]
  • Multi-Person Pose Estimation using Pose Residual Network. In this paper, we present MultiPoseNet ... method is implemented by the Pose Residual Network (PRN) which receives keypoint and person detections...
  • REACH

  • Referenced in 6 articles [sw00788]
  • force constants of a residue-scale elastic network model in single-domain proteins using...
  • SkipNet

  • Referenced in 2 articles [sw31369]
  • visual perception tasks, for many inputs shallower networks are sufficient. We exploit this observation ... basis. We introduce SkipNet, a modified residual network, that uses a gating network to selectively...
  • DeepXDE

  • Referenced in 61 articles [sw32456]
  • into the loss of the neural network using automatic differentiation. The PINN algorithm is simple ... forward problems. We propose a new residual-based adaptive refinement (RAR) method to improve...
  • FPINNs

  • Referenced in 27 articles [sw40570]
  • noisy data. PINNs employ standard feedforward neural networks (NNs) with the PDEs explicitly encoded into ... mean-squared PDE-residuals and the mean-squared error in initial/boundary conditions is minimized with...
  • UPSNet

  • Referenced in 1 article [sw39075]
  • paper, we propose a unified panoptic segmentation network (UPSNet) for tackling the newly proposed panoptic ... single backbone residual network, we first design a deformable convolution based semantic segmentation head...
  • TFLearn

  • Referenced in 1 article [sw21054]
  • prototyping through highly modular built-in neural network layers, regularizers, optimizers, metrics... Full transparency over ... Convolutions, LSTM, BiRNN, BatchNorm, PReLU, Residual networks, Generative networks... In the future, TFLearn is also...
  • FetchSGD

  • Referenced in 1 article [sw34099]
  • empirical effectiveness by training two residual networks and a transformer model. Subjects...
  • DeepRT

  • Referenced in 1 article [sw22012]
  • deep learning approach, an ensemble of Residual Network (ResNet) and Long Short-Term Memory (LSTM...
  • deep_speck

  • Referenced in 2 articles [sw34578]
  • present distinguishers based on deep residual neural networks that achieve a mean key rank roughly...
  • DiscretizationNet

  • Referenced in 6 articles [sw42183]
  • computation of PDE residuals, which are used to update network weights that result into converged...
  • CVDNet

  • Referenced in 1 article [sw41772]
  • propose CVDNet, a Deep Convolutional Neural Network (CNN) model to classify COVID-19 infection from ... proposed architecture is based on the residual neural network and it is constructed by using...