Recurrent Neural Networks for Missing or Asynchronous Data
Bengio, Yoshua, Gingras, Francois
–Neural Information Processing Systems
In this paper we propose recurrent neural networks with feedback into the input units for handling two types of data analysis problems. On the one hand, this scheme can be used for static data when some of the input variables are missing. On the other hand, it can also be used for sequential data, when some of the input variables are missing or are available at different frequencies.
Neural Information Processing Systems
Dec-31-1996