• InfoGAN

  • Referenced in 22 articles [sw40936]
  • information-theoretic extension to the Generative Adversarial Network that is able to learn disentangled representations ... completely unsupervised manner. InfoGAN is a generative adversarial network that also maximizes the mutual information...
  • mixup

  • Referenced in 11 articles [sw35857]
  • generalization of state-of-the-art neural network architectures. We also find that mixup reduces ... examples, and stabilizes the training of generative adversarial networks...
  • BEGAN

  • Referenced in 6 articles [sw31829]
  • BEGAN: Boundary Equilibrium Generative Adversarial Networks. We propose a new equilibrium enforcing method paired with ... distance for training auto-encoder based Generative Adversarial Networks. This method balances the generator...
  • KnockoffGAN

  • Referenced in 4 articles [sw42243]
  • Generating Knockoffs for Feature Selection using Generative Adversarial Networks. Feature selection is a pervasive problem ... knockoff generation model. We adapt the Generative Adversarial Networks framework to allow us to generate...
  • GANSim

  • Referenced in 4 articles [sw40967]
  • using an improved progressive growing of generative adversarial networks (GANs). Conditional facies modeling combines geological ... subsurface resources. Recently, researchers have used generative adversarial networks (GANs) for conditional facies modeling, where ... then appropriate latent vectors are searched to generate facies models that are consistent with...
  • GANomaly

  • Referenced in 5 articles [sw41240]
  • detection model, by using a conditional generative adversarial network that jointly learns the generation...
  • MaskGAN

  • Referenced in 3 articles [sw31828]
  • propose to improve sample quality using Generative Adversarial Networks (GANs), which explicitly train the generator...
  • Social GAN

  • Referenced in 2 articles [sw39577]
  • Social GAN: Socially Acceptable Trajectories with Generative Adversarial Networks. Understanding human motion behavior is critical ... combining tools from sequence prediction and generative adversarial networks: a recurrent sequence-to-sequence model...
  • MolGAN

  • Referenced in 3 articles [sw36059]
  • likelihood-based methods. Our method adapts generative adversarial networks (GANs) to operate directly on graph ... reinforcement learning objective to encourage the generation of molecules with specific desired chemical properties...
  • GAN Lab

  • Referenced in 2 articles [sw27149]
  • experts to learn and experiment with Generative Adversarial Networks (GANs), a popular class of complex ... With GAN Lab, users can interactively train generative models and visualize the dynamic training process...
  • MidiNet

  • Referenced in 1 article [sw36061]
  • MidiNet: A Convolutional Generative Adversarial Network for Symbolic-domain Music Generation. Most existing neural network ... DeepMind shows that convolutional neural networks (CNNs) can also generate realistic musical waveforms ... this light, we investigate using CNNs for generating melody (a series of MIDI notes ... distributions of melodies, making it a generative adversarial network (GAN). Moreover, we propose a novel...
  • DijetGAN

  • Referenced in 1 article [sw38858]
  • DijetGAN: A Generative-Adversarial Network Approach for the Simulation of QCD Dijet Events ... Generative-Adversarial Network (GAN) based on convolutional neural networks is used to simulate the production ... trained on events generated using MadGraph5 + Pythia8, and Delphes3 fast detector simulation. We demonstrate that...
  • SalGAN

  • Referenced in 1 article [sw28155]
  • SalGAN: Visual Saliency Prediction with Generative Adversarial Networks. We introduce SalGAN, a deep convolutional neural ... with adversarial examples. The first stage of the network consists of a generator model whose ... discriminator network trained to solve a binary classification task between the saliency maps generated ... generative stage and the ground truth ones. Our experiments show how adversarial training allows reaching...
  • StressGAN

  • Referenced in 1 article [sw41691]
  • unseen configurations. We propose a conditional generative adversarial network (cGAN) model for predicting ... solid structures. The cGAN learns to generate stress distributions conditioned by geometries, load, and boundary...
  • CovidGAN

  • Referenced in 1 article [sw41862]
  • optimistic. Deep learning networks like convolutional neural networks (CNNs) need a substantial amount of training ... images by developing an Auxiliary Classifier Generative Adversarial Network (ACGAN) based model called CovidGAN...
  • Keras-GAN

  • Referenced in 1 article [sw32552]
  • Collection of Keras implementations of Generative Adversarial Networks (GANs) suggested in research papers. These models...
  • HexaGAN

  • Referenced in 1 article [sw27773]
  • this paper, we propose HexaGAN, a generative adversarial network (GAN) framework that shows good classification...
  • MagNet

  • Referenced in 5 articles [sw41285]
  • framework for defending neural network classifiers against adversarial examples. MagNet does not modify the protected ... process for generating adversarial examples. MagNet includes one or more separate detector networks ... reformer network. Different from previous work, MagNet learns to differentiate between normal and adversarial examples ... does not rely on any process for generating adversarial examples, it has substantial generalization power...
  • Advbox

  • Referenced in 1 article [sw41290]
  • Advbox: a toolbox to generate adversarial examples that fool neural networks. In recent years, neural ... vulnerable to the attack of adversarial examples. Small and often imperceptible perturbations to the input ... toolbox to generate adversarial examples that fool neural networks in PaddlePaddle, PyTorch, Caffe2, MxNet, Keras...
  • SecML

  • Referenced in 2 articles [sw31336]
  • time evasion attacks to generate adversarial examples against deep neural networks, but also training-time...