Multiplicative Noise Channel in Generative Adversarial Networks
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- Type
- article
- Published
- 2017-10-01
- Cited by
- 3
- References
- 30
- OpenAlex
- https://openalex.org/W2770695261
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:9208866
Keywords
Adversarial system, Generative grammar, Multiplicative noise, Computer science, Multiplicative function
References
- Noise-enhanced convolutional neural networks
- Auto-Encoding Variational Bayes
- Neural correlations, population coding and computation
- Noise benefits in backpropagation and deep bidirectional pre-training
- Noise injection for training artificial neural networks: a comparison with weight decay and early stopping.
- Noise, neural codes and cortical organization.
- Training neural networks with additive noise in the desired signal
- Weight Uncertainty in Neural Network
- Bayesian Learning via Stochastic Gradient Langevin Dynamics
- Improved Techniques for Training GANs
- Generating Videos with Scene Dynamics
- SeqGAN: Sequence Generative Adversarial Nets with Policy Gradient
- Message Passing Multi-Agent GANs
- Learning from Simulated and Unsupervised Images through Adversarial Training
- Associate Latent Encodings in Learning from Demonstrations
- Least Squares Generative Adversarial Networks
- Triple Generative Adversarial Nets
- SEGAN: Speech Enhancement Generative Adversarial Network
- MAGAN: Margin Adaptation for Generative Adversarial Networks
- From Source to Target and Back: Symmetric Bi-Directional Adaptive GAN
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