Generative Adversarial Nets
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- Type
- article
- Published
- 2014-06-10
- Cited by
- 6,809
- References
- 39
- Access
- Open access
- OpenAlex
- https://openalex.org/W2099471712
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:276883628
Keywords
Adversarial system, Generative grammar, Computer science, Artificial intelligence
References
- Deep Boltzmann Machines
- Better Mixing via Deep Representations
- Information processing in dynamical systems: foundations of harmony theory
- Stochastic Backpropagation and Approximate Inference in Deep Generative Models
- Pylearn2: a machine learning research library
- Improving neural networks by preventing co-adaptation of feature detectors
- On pairwise costs for network flow multi-object tracking
- Auto-Encoding Variational Bayes
- SIGMa: simple greedy matching for aligning large knowledge bases
- On the convergence of markovian stochastic algorithms with rapidly decreasing ergodicity rates
- The "wake-sleep" algorithm for unsupervised neural networks.
- Extracting and composing robust features with denoising autoencoders
- Learning Deep Architectures for AI
- Characterization and computation of local Nash equilibria in continuous games
- Multi-Prediction Deep Boltzmann Machines
- Approximate inference for the loss-calibrated Bayesian
- Quickly Generating Representative Samples from an RBM-Derived Process
- ImageNet: A large-scale hierarchical image database
- Gradient-based learning applied to document recognition
- Training restricted Boltzmann machines using approximations to the likelihood gradient
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- A Transdisciplinary Review of Deep Learning Research and Its Relevance for Water Resources Scientists
- Deep learning for music generation: challenges and directions
- Building a state space for song learning
- E-swish: Adjusting Activations to Different Network Depths
- Generating and Refining Particle Detector Simulations Using the Wasserstein Distance in Adversarial Networks
- psfgan: a generative adversarial network system for separating quasar point sources and host galaxy light
- Pulling out all the tops with computer vision and deep learning
- ExpandNet: A Deep Convolutional Neural Network for High Dynamic Range Expansion from Low Dynamic Range Content
- Opening the black box of neural nets: case studies in stop/top discrimination
- Fast and Accurate Simulation of Particle Detectors Using Generative Adversarial Networks
- DiverseNet: When One Right Answer is not Enough
- Non-stationary texture synthesis by adversarial expansion
- Deep learning for determining a near-optimal topological design without any iteration
- Classifier-agnostic saliency map extraction
- ExoGAN: Retrieving Exoplanetary Atmospheres Using Deep Convolutional Generative Adversarial Networks
- Design of metalloproteins and novel protein folds using variational autoencoders
- Precise Simulation of Electromagnetic Calorimeter Showers Using a Wasserstein Generative Adversarial Network
- The Lund jet plane
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