generative adversarial networks with attention
Generative adversarial networks with attention refer to a type of artificial intelligence model that combines two components: a generator and a discriminator, which compete against each other to improve the model's performance. They also incorporate an attention mechanism, which enables the model to focus on specific parts of the input data, resulting in better output generation quality.
Requires login.
Related Concepts (1)
Similar Concepts
- adversarial autoencoders
- adversarial deep learning
- adversarial image synthesis
- adversarial networks
- adversarial text generation
- attention-based sequence-to-sequence models
- generalized adversarial loss
- generative adversarial network (gan) layers
- generative adversarial networks
- generative adversarial networks (gan)
- generative adversarial networks (gans)
- hierarchical attention networks
- multi-head attention
- recurrent neural networks with attention
- reinforcement learning with attention