Time Series and RNNs


Pilar Gómez-Gil, On the use of ‘Long Short Term Memory’ neural networks for time series prediction

Understanding LSTM Networks (blog)

Forecasting Short Time Series with LSTM Neural Networks, Oct 2016

Recurrent Neural Network Tutorial, Part 4 – Implementing a GRU/LSTM RNN with Python and Theano

RNNs in Tensorflow, a Practical Guide and Undocumented Features


Capacity and Trainability in Recurrent Neural Networks
Jasmine Collins, Jascha Sohl-Dickstein, David Sussillo

 A recurrent neural network without chaos
Thomas Laurent, James von Brecht

Quasi-Recurrent Neural Networks
James Bradbury, Stephen Merity, Caiming Xiong, Richard Socher

SampleRNN: An Unconditional End-to-End Neural Audio Generation Model
Soroush Mehri, Kundan Kumar, Ishaan Gulrajani, Rithesh Kumar, Shubham Jain, Jose Sotelo, Aaron Courville, Yoshua Beng

M Gemici et al., Generative Temporal Models with Memory

Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcasting

Generalized Method of Wavelet Moments

Structured Inference Networks for Nonlinear State Space Models


Anirudh Goyal, Alex Lamb, Ying Zhang, Saizheng Zhang, Aaron Courville and Yoshua Bengio, Professor Forcing: A New Algorithm for Training Recurrent Networks, in: Advances in Neural Information Processing Systems 29 (NIPS 2016), pages 4601--4609, Curran Associates, Inc., 2016

Felix A. Gers , Douglas Eck , Jürgen Schmidhuber, Applying LSTM to Time Series Predictable through Time-Window Approaches

Jan Koutník, Klaus Greff, Faustino Gomez, Jürgen Schmidhuber, A Clockwork RNN, Feb 2014