Grid long short-term memory neural networks

One or more non-transitory computer storage media storing instructions that when executed by one or more computers cause the one or more computers to implement:

• a grid Long Short-Term Memory (LSTM) neural network, wherein the grid LSTM neural network comprises a plurality of N-LSTM blocks arranged in an N-dimensional grid, wherein N is an integer greater than zero, and wherein each N-LSTM block is configured to:
• receive N input hidden vectors, the N input hidden vectors each corresponding to a respective one of the N dimensions;
• receive N input memory vectors, the N input memory vectors each corresponding to a respective one of the N dimensions;
• and
• for each of the dimensions, apply a respective transform for the dimension to the memory hidden vector corresponding to the dimension and the input hidden vector corresponding to the dimension to generate a new hidden vector corresponding to the dimension and a new memory vector corresponding to the dimension.

A method for processing a neural network input to generate a neural network output by processing the neural network input using a grid Long Short-Term Memory (LSTM) neural network, wherein the grid LSTM neural network comprises a plurality of N-LSTM blocks arranged in an N-dimensional grid, wherein N is an integer greater than zero, and wherein the method comprises, for each N-LSTM block:

• receiving N input hidden vectors, the N input hidden vectors each corresponding to a respective one of the N dimensions;
• receiving N input memory vectors, the N input memory vectors each corresponding to a respective one of the N dimensions;
• and
• for each of the dimensions, applying a respective transform for the dimension to the memory hidden vector corresponding to the dimension and the input hidden vector corresponding to the dimension to generate a new hidden vector corresponding to the dimension and a new memory vector corresponding to the dimension.