• AlexNet

  • Referenced in 542 articles [sw38522]
  • AlexNet is a convolutional neural network that is 8 layers deep. You can load ... pretrained version of the network trained on more than a million images from the ImageNet ... database [1]. The pretrained network can classify images into 1000 object categories, such as keyboard ... many animals. As a result, the network has learned rich feature representations for a wide...
  • SparseMatrix

  • Referenced in 747 articles [sw04629]
  • chemical process simulation, mathematics and statistics, power networks, and other networks and graphs). We provide...
  • CRAN

  • Referenced in 570 articles [sw04351]
  • homepage for further information. CRAN is a network of ftp and web servers around ... CRAN mirror nearest to you to minimize network load...
  • TensorFlow

  • Referenced in 653 articles [sw15170]
  • conducting machine learning and deep neural networks research, but the system is general enough...
  • WordNet

  • Referenced in 410 articles [sw01777]
  • conceptual-semantic and lexical relations. The resulting network of meaningfully related words and concepts ... close proximity to one another in the network are semantically disambiguated. Second, WordNet labels...
  • Mosek

  • Referenced in 509 articles [sw04618]
  • Medical and hospital management, Power supply and network planning, Logistics, TV commercial scheduling, Structural engineering...
  • ANFIS

  • Referenced in 285 articles [sw08730]
  • ANFIS: adaptive-network-based fuzzy inference system. The architecture and learning procedure underlying ANFIS (adaptive ... network-based fuzzy inference system) is presented, which is a fuzzy inference system implemented ... framework of adaptive networks. By using a hybrid learning procedure, the proposed ANFIS can construct ... yielding remarkable results. Comparisons with artificial neural networks and earlier work on fuzzy modeling...
  • darch

  • Referenced in 321 articles [sw11086]
  • This package is for generating neural networks with many layers (deep architectures) and train them ... Reducing the dimensionality of data with neural networks” (G. E. Hinton, R. R. Salakhutdinov). This...
  • Concorde

  • Referenced in 319 articles [sw04770]
  • traveling salesman problem (TSP) and some related network optimization problems. The code is written ... solver includes code for running over networks of UNIX workstations...
  • PyTorch

  • Referenced in 440 articles [sw20939]
  • PyTorch python package: Tensors and Dynamic neural networks in Python with strong GPU acceleration. PyTorch...
  • ScaLAPACK

  • Referenced in 421 articles [sw00830]
  • distributed memory message-passing MIMD computers and networks of workstations supporting parallel virtual machine...
  • Scatter Search

  • Referenced in 297 articles [sw05291]
  • application to the problem of training neural networks. Scatter search is an evolutionary method that ... optimal weight values in a multilayer neural network. Through experimentation, we show that our instantiation...
  • FORM

  • Referenced in 347 articles [sw09051]
  • TFORM) and distributed computations on a network (ParFORM). See also: http://dx.doi.org/10.1016/j.cpc.2012.12.028...
  • Neural Network Toolbox

  • Referenced in 178 articles [sw07378]
  • Neural Network Toolbox. Neural Network Toolbox™ provides functions and apps for modeling complex nonlinear systems ... modeled with a closed-form equation. Neural Network Toolbox supports supervised learning with feedforward, radial ... basis, and dynamic networks. It also supports unsupervised learning with self-organizing maps and competitive ... design, train, visualize, and simulate neural networks. You can use Neural Network Toolbox for applications...
  • SNAP

  • Referenced in 179 articles [sw04184]
  • Stanford Network Analysis Platform (SNAP) is a general purpose, high performance system for analysis ... manipulation of large networks. Graphs consists of nodes and directed/undirected/multiple edges between the graph nodes ... Networks are graphs with data on nodes and/or edges of the network. The core SNAP ... graph representation. It easily scales to massive networks with hundreds of millions of nodes...
  • Keras

  • Referenced in 210 articles [sw15491]
  • Keras is a minimalist, highly modular neural networks library, written in Python and capable ... modularity, minimalism, and extensibility). supports both convolutional networks and recurrent networks, as well as combinations...
  • ns-2

  • Referenced in 194 articles [sw11690]
  • Network Simulator - ns-2. Ns is a discrete event simulator targeted at networking research ... over wired and wireless (local and satellite) networks. Ns began as a variant ... REAL network simulator in 1989 and has evolved substantially over the past few years...
  • NEURON

  • Referenced in 189 articles [sw03059]
  • Parallel network simulations with NEURON. The NEURON simulation environment has been extended to support parallel ... network simulations. Each processor integrates the equations for its subnet over an interval equal ... connection delay. The performance of three published network models with very different spike patterns exhibits ... magnitude makes practical the running of large network simulations that could otherwise not be explored...
  • DGM

  • Referenced in 185 articles [sw39282]
  • approximating the solution with a deep neural network which is trained to satisfy the differential ... Instead of forming a mesh, the neural network is trained on batches of randomly sampled ... with the solution approximated by a neural network instead of a linear combination of basis ... theorem regarding the approximation power of neural networks for a class of quasilinear parabolic PDEs...
  • gss

  • Referenced in 317 articles [sw06099]
  • Internet on CRAN, the Comprehensive R Archive Network. The use of gss facilities is illustrated...