• ToulBar2

  • Referenced in 22 articles [sw07289]
  • software for Graphical Models such as Cost Function Networks, Markov Random Fields, Weighted Constraint Satisfaction...
  • NETGEN

  • Referenced in 151 articles [sw09229]
  • capacitated and uncapacitated transportation and minimum cost flow network problems, and assignment problems. In addition ... generating structurally different classes of network problems the code permits the user to vary structural ... paper contains the solution time and objective function value of 40 assignment, transportation, and network...
  • D-ADMM

  • Referenced in 25 articles [sw28440]
  • ADMM), for solving separable optimization problems in networks of interconnected nodes or agents ... optimization problem there is a private cost function and a private constraint set at each ... minimize the sum of all the cost functions, constraining the solution ... ADMM is proven to converge when the network is bipartite or when all the functions...
  • AutoKeras

  • Referenced in 7 articles [sw33648]
  • suffer from expensive computational cost. Network morphism, which keeps the functionality of a neural network...
  • GREAT

  • Referenced in 1 article [sw18878]
  • find regions of topological or functional similarities between networks. In computational biology ... between nodes in different networks (via a node cost function) and then aim to find ... networks) with respect to “node conservation”, typically the total node cost function over all aligned ... optimally edges between networks first in order to improve node cost function needed to then...
  • WaveGlow

  • Referenced in 4 articles [sw35020]
  • only a single network, trained using only a single cost function: maximizing the likelihood...
  • Lasagne

  • Referenced in 7 articles [sw20936]
  • such as Convolutional Neural Networks (CNNs), recurrent networks including Long Short-Term Memory (LSTM ... momentum, RMSprop and ADAM. Freely definable cost function and no need to derive gradients...
  • automl

  • Referenced in 3 articles [sw32865]
  • networks either with gradient descent or metaheuristic, using automatic hyper parameters tuning and custom cost ... function. A mix inspired by the common tricks on Deep Learning and Particle Swarm Optimization...
  • MONC

  • Referenced in 7 articles [sw00589]
  • computations for Monte Carlo methods within a network of personal computers using the program system ... modification of a congruent pseudorandom number generator; functional capabilities of the MONC; demands ... execute using the MONC; an estimate of costs of distributed computations using the MONC. Advantages...
  • LinkBoost

  • Referenced in 1 article [sw29981]
  • communities in a network. Specifically, a variable-cost loss function is defined to address ... function. As a result, any link prediction method designed to optimize the loss function would ... function and present an approach to scale-up the algorithm by decomposing the network into...
  • iCDI-PseFpt

  • Referenced in 15 articles [sw30067]
  • with PseAAC and molecular fingerprints. Many crucial functions in life, such as heartbeat, sensory transduction ... study of ion channel-drug interaction networks is an important topic for drug development. However ... both time-consuming and costly to determine whether a drug and a protein ion channel...
  • PANET

  • Referenced in 1 article [sw25676]
  • networks. Despite such a useful function, limitations on the network size that can be analyzed ... exist due to high computational costs. In addition, the plugin cannot verify an intrinsic property ... function to simulate the observation on a large number of random networks. To overcome these...
  • MERLIN

  • Referenced in 14 articles [sw04248]
  • training of neural networks. Minimizing a multidimensional function faces a lot of difficulties. There ... derivatives using differencing, that in turn costs in computing time as well as in accuracy...
  • PoliUniPool

  • Referenced in 3 articles [sw42440]
  • service; (5) the system estimates the costs for each user, in order ... system has some social network functionalities, e.g. drivers are able to set partial pre-arranged...
  • FINN-R

  • Referenced in 1 article [sw25906]
  • inference engines on FPGAs. Given a neural network description, the tool optimizes for given platforms ... precision. We introduce formalizations of resource cost functions and performance predictions, and elaborate ... evaluate a selection of reduced precision neural networks ranging from CIFAR-10 classifiers to YOLO...
  • JESS

  • Referenced in 1 article [sw38849]
  • paradigm that brings cost efficiency and flexibility through software-defined functions resident on centralized controllers ... related technologies still under development, operational SDN networks already face major security threats. Therefore, comprehensive...
  • CAPP

  • Referenced in 9 articles [sw03233]
  • reasons for this effect are: Costs are declining, which encourages partnerships between CAD and CAPP ... from one point to another on the network; and relational databases (RDBs) and associated structured ... planning. An alternative way of accomplishing this function was needed and Computer Aided Process Planning ... planning applicationMetCAPP software looks for the least costly plan capable of producing the design...
  • DeepMovie

  • Referenced in 1 article [sw15171]
  • another image. First, they use convolutional neural network features to build a statistical model ... incorporate optical flow explicitly into the cost function...
  • EGAD

  • Referenced in 1 article [sw39967]
  • EGAD: ultra-fast functional analysis of gene networks. Evaluating gene networks with respect to known ... computationally costly one. Many computational experiments are difficult to apply exhaustively in network analysis ... gene networks, we have implemented a set of very efficient tools to calculate functional properties...
  • EpidemiOptim

  • Referenced in 1 article [sw40126]
  • optimization. EpidemiOptim turns epidemiological models and cost functions into optimization problems via a standard interface ... algorithms based on QLearning with deep neural networks ( extsc{dqn}) and evolutionary algorithms ( extsc{nsga ... economists) can easily compare epidemiological models, costs functions and optimization algorithms to address important choicesto...