Mapa mental
Deep Learning Mechanisms
Conteúdo do mapa
Deep Learning Mechanisms
Attention Mechanism
- In Encoder/Decoder Networks, it allows the Decoder to "Pay Attention" to different parts of the input
- RNN
- Pay attention to different part of Input at every step of output sequence generation
- Each decoder output depends on a weighted combination of ALL THE INPUT STATES, not just the last state
- Each input state is assigned an attention weight for each output step (in a sequence of outputs for an RNN)
- Each decoder output depends on a weighted combination of ALL THE INPUT STATES, not just the last state
- Pay attention to different part of Input at every step of output sequence generation
- RNN
- In Encoder/Decoder Networks, it allows the Decoder to "Pay Attention" to different parts of the input
Backpropagation
Sparsely Attentive Backtracking (SAB)
Informações
- Descrição
- Mapa Mental sobre Deep Learning Mechanisms, criado por Sophokles Ktistakis em 26-11-2018.
- Criado por
- Sophokles Ktistakis
- Visualizações
- 0
- Avaliação