Encoder-decoder neural networks

Thesis

This thesis introduces the concept of an encoder-decoder neural network and develops architectures for the construction of such networks. Encoder-decoder neural networks are probabilistic conditional generative models of high-dimensional structured items such as natural language utterances and natural images. Encoder-decoder neural networks estimate a probability distribution over structured items belonging to a target set conditioned on structured items belonging to a source set....

Expand abstract

Authors: Kalchbrenner, N

• Type of award: DPhil
• Level of award: Doctoral
• Awarding institution: University of Oxford
• Language: English
• Keywords: Deep Learning; Neural Machine Translation; Autoregressive Generative Models
• Subjects: Artificial intelligence