• Scatter Search

  • Referenced in 286 articles [sw05291]
  • application to the problem of training neural networks. Scatter search is an evolutionary method that ... when searching for optimal weight values in a multilayer neural network. Through experimentation, we show...
  • WGCNA

  • Referenced in 17 articles [sw07123]
  • package WGCNA: Weighted Correlation Network Analysis. Functions necessary to perform Weighted Correlation Network Analysis...
  • KONECT

  • Referenced in 37 articles [sw17480]
  • directed, undirected, unipartite, bipartite, weighted, unweighted, signed and temporal networks collected from...
  • ToulBar2

  • Referenced in 22 articles [sw07289]
  • Models such as Cost Function Networks, Markov Random Fields, Weighted Constraint Satisfaction Problems, Weighted...
  • BinaryConnect

  • Referenced in 13 articles [sw35871]
  • BinaryConnect: Training Deep Neural Networks with binary weights during propagations. Deep Neural Networks (DNN) have ... dedicated hardware for Deep Learning (DL). Binary weights, i.e., weights which are constrained to only ... networks. We introduce BinaryConnect, a method which consists in training a DNN with binary weights...
  • CIXL2

  • Referenced in 19 articles [sw03302]
  • problem of obtaining the weight of each network in a ensemble of neural networks...
  • BinaryNet

  • Referenced in 9 articles [sw35872]
  • Binarized Neural Networks: Training Deep Neural Networks with Weights and Activations Constrained ... Binarized Neural Networks (BNNs) - neural networks with binary weights and activations at run-time...
  • MCODE

  • Referenced in 45 articles [sw35748]
  • interaction networks that may represent molecular complexes. The method is based on vertex weighting ... interest without considering the rest of the network and allows examination of cluster interconnectivity, which...
  • MMG

  • Referenced in 4 articles [sw29328]
  • usually related through a complex (weighted) network of interactions, and often the more pertinent question ... easily incorporate information about weights in the network, is robust against missing data...
  • AIS-BN

  • Referenced in 25 articles [sw02223]
  • networks, (2) a smooth learning method for the importance function, and (3) a dynamic weighting ... weighting and self-importance sampling. We used in our tests three large real Bayesian network...
  • DistAl

  • Referenced in 99 articles [sw01746]
  • pattern classification systems. A new constructive neural network learning algorithm (DistAl) based on inter-pattern ... patterns belonging to the same class. The weights and thresholds of the hidden neurons...
  • PMTBR

  • Referenced in 17 articles [sw02086]
  • contexts of frequency weighting, circuit simulation with parasitics networks having large numbers of input/output ports...
  • LS-SVMlab

  • Referenced in 26 articles [sw07367]
  • unsupervised learning, recurrent networks and control are available. Robustness, sparseness and weightings can be incorporated...
  • jHoles

  • Referenced in 6 articles [sw15020]
  • tool for understanding biological complex networks via clique weight rank persistent homology. Complex networks equipped ... studying the connectivity features of complex networks. jHoles fills the lack of an efficient implementation ... filtering process for clique weight rank homology. We will give a brief overview of Holes ... implementation and the problem of clique weight rank homology. We present a biological case study...
  • HEWN

  • Referenced in 3 articles [sw02189]
  • CLIQUE problem. A Hierarchical Edge-Weighted Network (HEWN) which is equivalent to the corresponding Maximum...
  • pyunicorn

  • Referenced in 4 articles [sw19314]
  • spatial networks, networks of interacting networks, node-weighted statistics or network surrogates. Additionally, pyunicorn provides...
  • PRED-CLASS

  • Referenced in 5 articles [sw26873]
  • reducing the number of free parameters (network synaptic weights) for faster training, improved generalization...
  • MicroGrid

  • Referenced in 11 articles [sw09654]
  • network simulator to the simulation of large networks. These techniques employ a sophisticated graph partitioner ... edge and node weighting schemes exploiting a range of static network and dynamic application information...
  • gergm

  • Referenced in 3 articles [sw21317]
  • Stochastic Weighted Graphs: Flexible Model Specification and Simulation. In most domains of network analysis researchers ... that arise in nature with weighted edges. Such networks are routinely dichotomized in the interest ... using available methods for statistical inference with networks. The generalized exponential random graph model (GERGM ... simulate and model the edges of a weighted graph. The GERGM specifies a joint distribution...
  • LabelRankT

  • Referenced in 3 articles [sw20731]
  • binary networks, LabelRankT works on weighted and directed networks, which provides a flexible and promising...