14. A system comprising one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: obtaining a set of first word sequences, wherein the set of first word sequences comprises a plurality of first sequences of words and, for each first sequence of words, a word that follows a last word in the first sequence of words, wherein each first word sequence in the set has been classified as being authored by a first author; processing the plurality of first sequences of words using a trained neural network system to determine an author vector for the first author, wherein the author vector characterizes the first author; after determining the author vector for the first author, obtaining a second word sequence that was authored by the first author; and using the author vector for the first author to predict a next word that follows a last word in the second word sequence.
14. A system comprising one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: obtaining a set of first word sequences, wherein the set of first word sequences comprises a plurality of first sequences of words and, for each first sequence of words, a word that follows a last word in the first sequence of words, wherein each first word sequence in the set has been classified as being authored by a first author; processing the plurality of first sequences of words using a trained neural network system to determine an author vector for the first author, wherein the author vector characterizes the first author; after determining the author vector for the first author, obtaining a second word sequence that was authored by the first author; and using the author vector for the first author to predict a next word that follows a last word in the second word sequence. 15. The system of claim 14 , wherein: the trained neural network system has been trained to receive a current sequence of words authored by a current author and to generate a respective word score for each word in a pre-determined set of words, wherein each of the respective word scores represents a predicted likelihood that the corresponding word follows a last word in the current sequence of words, and determining the author vector for the first author using the trained neural network system comprises iteratively providing each of the plurality of first sequences of words to the trained neural network system to determine the author vector for the first author using gradient descent.